HW4 - High income household prediction
acs <- read.table("http://jaredlander.com/data/acs_ny.csv",sep=",",
header=TRUE, stringsAsFactors=TRUE)Load the necessary libraries
library(ggplot2)
library(useful)
library(caret)## Loading required package: latticelibrary(ISLR)
library(scales)
library(plyr)
library(rpart)
library(rpart.plot)
library(class)
library(MuMIn)Let’s assume our goal is to build a model to predict if household income is greater than $250,000 per year.
Task 1: Data preparation
We start by building a binary response variable.
acs$HighIncome <- as.numeric(with(acs, FamilyIncome >= 250000))
head(acs)## Acres FamilyIncome FamilyType NumBedrooms NumChildren NumPeople
## 1 1-10 150 Married 4 1 3
## 2 1-10 180 Female Head 3 2 4
## 3 1-10 280 Female Head 4 0 2
## 4 1-10 330 Female Head 2 1 2
## 5 1-10 330 Male Head 3 1 2
## 6 1-10 480 Male Head 0 3 4
## NumRooms NumUnits NumVehicles NumWorkers OwnRent YearBuilt
## 1 9 Single detached 1 0 Mortgage 1950-1959
## 2 6 Single detached 2 0 Rented Before 1939
## 3 8 Single detached 3 1 Mortgage 2000-2004
## 4 4 Single detached 1 0 Rented 1950-1959
## 5 5 Single attached 1 0 Mortgage Before 1939
## 6 1 Single detached 0 0 Rented Before 1939
## HouseCosts ElectricBill FoodStamp HeatingFuel Insurance Language
## 1 1800 90 No Gas 2500 English
## 2 850 90 No Oil 0 English
## 3 2600 260 No Oil 6600 Other European
## 4 1800 140 No Oil 0 English
## 5 860 150 No Gas 660 Spanish
## 6 700 140 No Gas 0 English
## HighIncome
## 1 0
## 2 0
## 3 0
## 4 0
## 5 0
## 6 0tail(acs)## Acres FamilyIncome FamilyType NumBedrooms NumChildren NumPeople
## 22740 10+ 556250 Married 4 0 2
## 22741 10+ 565000 Married 5 3 5
## 22742 10+ 599000 Married 4 0 2
## 22743 10+ 611700 Married 4 1 5
## 22744 10+ 621430 Married 3 2 4
## 22745 10+ 751200 Married 4 2 4
## NumRooms NumUnits NumVehicles NumWorkers OwnRent YearBuilt
## 22740 10 Single detached 2 1 Mortgage Before 1939
## 22741 10 Single detached 2 2 Mortgage 1990-1999
## 22742 6 Single detached 2 2 Mortgage Before 1939
## 22743 9 Single detached 5 3 Mortgage Before 1939
## 22744 11 Single detached 2 3 Mortgage 1970-1979
## 22745 10 Single detached 2 2 Mortgage 1940-1949
## HouseCosts ElectricBill FoodStamp HeatingFuel Insurance Language
## 22740 1800 380 No Oil 1700 English
## 22741 1700 370 No Gas 1000 English
## 22742 1300 100 No Gas 3500 English
## 22743 410 100 No Oil 1300 Spanish
## 22744 1600 80 No Gas 800 Spanish
## 22745 6500 400 No Oil 2000 English
## HighIncome
## 22740 1
## 22741 1
## 22742 1
## 22743 1
## 22744 1
## 22745 1Before splitting data, I am going to add/modify some variables for use in my models
- Food Stamp to binary integer for linear regression
- Own home to binary integer for linear regression
- Family type to numerical for linear regression later
acs$foodstamp_binary <- ifelse(acs$FoodStamp == "Yes",1,0) # (yes = 1, no = 0)
# Option 2 for doing this - I did not use this. Does not add new column but modifes exisiting column
# levels(acs$FoodStamp) <- c("0","1")
acs$own_home <- ifelse(acs$OwnRent == "Rented",0, ifelse(acs$FamilyIncome == "Mortgage",1,2)) # (own = 1, rent = 0)
acs$family_type_cat <- ifelse(acs$FamilyType == "Married",1, ifelse(acs$FamilyIncome == "Female Head",2,3))
# married = 1, male head = 2, female head = 3Based on groupby and plots (completed later) create new variables for potential use
acs$InsuranceHigh <- (acs$Insurance > 1000) * 1
acs$NumWorkers2 <- (acs$NumWorkers == 2) * 1
acs$HouseCostsHigh <- (acs$HouseCosts > 1000) * 1
acs$high_electric <- (acs$ElectricBill > 350) * 1Break it into a training and test set with an 80/20 split.
set.seed(447)
testrecs <- sample(nrow(acs),0.2 * nrow(acs))
acs_test <- acs[testrecs,]
acs_fit <- acs[-testrecs,] Create binary variable where 1 = not on food stamps & not renting & married
acs$HI_pred1 <- 0
acs$HI_pred1[acs_test$FoodStamp == 'No' & acs_test$OwnRent != 'Rented' & acs_test$FamilyType == 'Married'] <- 1# I like this visualization for a quick visual of what I'm dealing with before digging in (modified from class notes)
ggplot(acs,aes(x=FamilyIncome)) + geom_density(fill="#31a354", color="#31a354") +
geom_vline(xintercept=250000) + scale_x_continuous(label=multiple.dollar, limits=c(0,1000000))## Warning: Removed 13 rows containing non-finite values (stat_density).
Interesting test I found for testing data normality - downside is it has a 5000 observation limit
If p-value is less than .05 (or chosen significance level) then sample is NOT normally distributed This is not relevant here, but worth keeping for future The plot shows that there is a clear left skewned distribution - expected but still nice to include
shapiro.test(acs_test$FamilyIncome)##
## Shapiro-Wilk normality test
##
## data: acs_test$FamilyIncome
## W = 0.71538, p-value < 2.2e-16Task 2: Preliminary EDA and feature engineering
Before trying to build any classification models, you should do some exploratory data analysis to try to get a sense of which variables might be useful for trying to predict cases where FamilyIncome >= 250000. You should use a combination of group by analysis (i.e. plyr or dplyr or similar) and plotting.
If you decide you’d like to create some new variables (feature engineering), feel free to do that. Just document what you did and why you did it.
# Get some summary stats on each variable
summary(acs_fit)## Acres FamilyIncome FamilyType NumBedrooms
## 10+ : 815 Min. : 50 Female Head: 2594 Min. :0.000
## 1-10 : 3709 1st Qu.: 53000 Male Head : 907 1st Qu.:3.000
## Sub 1:13672 Median : 87100 Married :14695 Median :3.000
## Mean : 110726 Mean :3.384
## 3rd Qu.: 134082 3rd Qu.:4.000
## Max. :1605000 Max. :8.000
##
## NumChildren NumPeople NumRooms NumUnits
## Min. : 0.0000 Min. : 2.0 Min. : 1.00 Mobile home : 583
## 1st Qu.: 0.0000 1st Qu.: 2.0 1st Qu.: 6.00 Single attached: 1916
## Median : 0.0000 Median : 3.0 Median : 7.00 Single detached:15697
## Mean : 0.9013 Mean : 3.4 Mean : 7.18
## 3rd Qu.: 2.0000 3rd Qu.: 4.0 3rd Qu.: 8.00
## Max. :12.0000 Max. :18.0 Max. :21.00
##
## NumVehicles NumWorkers OwnRent YearBuilt
## Min. :0.000 Min. :0.000 Mortgage:16074 Before 1939:4874
## 1st Qu.:2.000 1st Qu.:1.000 Outright: 128 1950-1959 :3107
## Median :2.000 Median :2.000 Rented : 1994 1960-1969 :2201
## Mean :2.119 Mean :1.748 1970-1979 :1894
## 3rd Qu.:3.000 3rd Qu.:2.000 1990-1999 :1647
## Max. :6.000 Max. :3.000 1980-1989 :1598
## (Other) :2875
## HouseCosts ElectricBill FoodStamp HeatingFuel
## Min. : 4 Min. : 1.0 No :16777 Gas :10899
## 1st Qu.: 650 1st Qu.:100.0 Yes: 1419 Oil : 5187
## Median :1200 Median :150.0 Wood : 986
## Mean :1480 Mean :174.4 Electricity: 831
## 3rd Qu.:2000 3rd Qu.:220.0 Other : 148
## Max. :7090 Max. :580.0 Coal : 124
## (Other) : 21
## Insurance Language HighIncome
## Min. : 0.0 Asian Pacific : 639 Min. :0.00000
## 1st Qu.: 400.0 English :14262 1st Qu.:0.00000
## Median : 720.0 Other : 225 Median :0.00000
## Mean : 958.9 Other European: 1640 Mean :0.06139
## 3rd Qu.:1200.0 Spanish : 1430 3rd Qu.:0.00000
## Max. :6600.0 Max. :1.00000
##
## foodstamp_binary own_home family_type_cat InsuranceHigh
## Min. :0.00000 Min. :0.000 Min. :1.000 Min. :0.000
## 1st Qu.:0.00000 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:0.000
## Median :0.00000 Median :2.000 Median :1.000 Median :0.000
## Mean :0.07798 Mean :1.781 Mean :1.385 Mean :0.326
## 3rd Qu.:0.00000 3rd Qu.:2.000 3rd Qu.:1.000 3rd Qu.:1.000
## Max. :1.00000 Max. :2.000 Max. :3.000 Max. :1.000
##
## NumWorkers2 HouseCostsHigh high_electric
## Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :1.0000 Median :0.00000
## Mean :0.4768 Mean :0.5433 Mean :0.06666
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.0000 Max. :1.00000
## Histogram
# see that those that those that own home correlate with higher incomes overall
ggplot(acs_fit) + geom_histogram(aes(x=own_home), fill = "gray")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Scatterplots
# scatter number of workers and family income
ggplot(data=acs_fit) + geom_point(aes(x=NumWorkers, y=FamilyIncome))
# scatter plot shows that those not on foodstamps tend to have higher income = duh, but relevant for model later
ggplot(data=acs_fit) + geom_point(aes(x=foodstamp_binary, y=FamilyIncome))
# plot shows that homes with 2 workers correlate with higher incomes vs other number of workers
ggplot(data=acs_fit) + geom_point(aes(x=NumWorkers, y=FamilyIncome))
# notice that there are very few observations with male head type. Female head has lower income and married highest incomes
ggplot(data=acs_fit) + geom_point(aes(x=family_type_cat, y=FamilyIncome))
# scatter house costs and family income - see that higher house costs correlate to higher incomes (slightly) - nothin major though
ggplot(data=acs_fit) + geom_point(aes(x=HouseCosts, y=FamilyIncome))
# create matrix of scatterplots
# pairs(acs[,1:19])Boxplot
coor_cartesian -> Setting limits on the coordinate system will zoom the plot (like you’re looking at it with a magnifying glass), and will not change the underlying data like setting limits on a scale will.
# See that outliers begin roughly around income of $100,000
ggplot(data=acs_fit) + geom_boxplot(aes(x=NumWorkers, y=FamilyIncome)) + coord_cartesian(ylim = c(0, 350000))## Warning: Continuous x aesthetic -- did you forget aes(group=...)?
Density Plots
These show the density by variable on axis. These are useful to see the concentration range of values
ggplot(acs_fit) + geom_density(aes(x=acs_fit$FamilyIncome)) + scale_x_continuous(labels=dollar)
ggplot(acs_fit) + geom_density(aes(x=acs_fit$HouseCosts)) + scale_x_continuous(labels=dollar)
ggplot(acs_fit) + geom_density(aes(x=acs_fit$NumChildren)) + scale_x_continuous()
ggplot(acs_fit) + geom_density(aes(x=acs_fit$FamilyIncome)) + scale_x_log10(breaks =c(100,1000,10000,100000), labels=dollar) + annotation_logticks(sides="bt")
ggplot(acs_fit) + geom_density(aes(x=acs_fit$HouseCosts)) + scale_x_log10(breaks =c(100,1000,10000,100000), labels=dollar) + annotation_logticks(sides="bt")
# Misc Plots
# shows positive correlation between insurance and family income
ggplot(acs_fit, aes(x=acs_fit$Insurance, y=acs_fit$FamilyIncome)) +geom_point() + geom_smooth()## `geom_smooth()` using method = 'gam'
# density plot for electrical bil
ggplot(acs_fit) + geom_density(aes(x=acs_fit$ElectricBill)) + scale_x_log10(breaks =c(100,1000,10000,100000), labels=dollar) + annotation_logticks(sides="bt")
# shows positive correlation between electric bill and family income
ggplot(acs_fit, aes(x=acs_fit$ElectricBill, y=acs_fit$FamilyIncome)) +geom_point() + geom_smooth()## `geom_smooth()` using method = 'gam'
Group by analysis
# This shows a good spread or range of each family type group. This will lend itself well to being included in my analysis
ddply(acs_fit,.(FamilyType),summarise,family_type_count=length(FamilyIncome))## FamilyType family_type_count
## 1 Female Head 2594
## 2 Male Head 907
## 3 Married 14695# Interesting look at mean income of family type grouped with home ownership type
ddply(acs_fit,.(FamilyType,OwnRent), summarise, mean_income=mean(FamilyIncome))## FamilyType OwnRent mean_income
## 1 Female Head Mortgage 69983.15
## 2 Female Head Outright 92303.57
## 3 Female Head Rented 34258.14
## 4 Male Head Mortgage 79298.16
## 5 Male Head Outright 213250.00
## 6 Male Head Rented 47620.92
## 7 Married Mortgage 126152.48
## 8 Married Outright 110020.36
## 9 Married Rented 71331.00ddply(acs_fit,.(FamilyType,FoodStamp), summarise, mean_income=mean(FamilyIncome))## FamilyType FoodStamp mean_income
## 1 Female Head No 67144.55
## 2 Female Head Yes 37105.47
## 3 Male Head No 78679.59
## 4 Male Head Yes 45825.75
## 5 Married No 124832.07
## 6 Married Yes 61612.91# simple look at mean income by foodstamp. Obvious results, but at the same time surprising to find that mean income
# for those on food stamps in near $50k
ddply(acs_fit,.(FoodStamp), summarise, mean_income=mean(FamilyIncome))## FoodStamp mean_income
## 1 No 115898.77
## 2 Yes 49572.72ddply(acs_fit,.(FoodStamp,NumBedrooms), summarise, mean_income=mean(FamilyIncome), num_bedrooms=mean(NumBedrooms))## FoodStamp NumBedrooms mean_income num_bedrooms
## 1 No 0 91092.92 0
## 2 No 1 68606.42 1
## 3 No 2 80216.78 2
## 4 No 3 102048.19 3
## 5 No 4 137687.35 4
## 6 No 5 173357.12 5
## 7 No 8 182832.27 8
## 8 Yes 0 36577.50 0
## 9 Yes 1 22038.06 1
## 10 Yes 2 33118.22 2
## 11 Yes 3 45066.36 3
## 12 Yes 4 62828.82 4
## 13 Yes 5 60499.15 5
## 14 Yes 8 82773.62 8# This is a little excessive, but would be useful for piping it to a csv file (for example) if relevant to tasks at hand
ddply(acs,.(NumBedrooms,NumChildren,NumPeople,NumRooms,NumUnits,NumVehicles,NumWorkers), summarise, mean_income=mean(FamilyIncome))## NumBedrooms NumChildren NumPeople NumRooms NumUnits
## 1 0 0 2 1 Single attached
## 2 0 0 2 1 Single detached
## 3 0 0 2 1 Single detached
## 4 0 0 2 1 Single detached
## 5 0 0 2 1 Single detached
## 6 0 0 2 1 Single detached
## 7 0 0 2 2 Mobile home
## 8 0 0 2 2 Single attached
## 9 0 0 2 2 Single detached
## 10 0 0 3 1 Single detached
## 11 0 0 3 3 Single detached
## 12 0 0 4 1 Single detached
## 13 0 0 4 3 Single detached
## 14 0 0 6 1 Single attached
## 15 0 1 3 1 Single attached
## 16 0 1 3 1 Single detached
## 17 0 1 3 2 Mobile home
## 18 0 1 3 2 Single detached
## 19 0 1 4 1 Single detached
## 20 0 1 4 2 Single detached
## 21 0 2 4 1 Single detached
## 22 0 2 4 1 Single detached
## 23 0 2 4 1 Single detached
## 24 0 2 4 2 Single detached
## 25 0 2 5 1 Single detached
## 26 0 2 5 2 Single detached
## 27 0 3 4 1 Single detached
## 28 0 3 5 2 Single detached
## 29 0 3 6 1 Mobile home
## 30 1 0 2 2 Mobile home
## 31 1 0 2 2 Single attached
## 32 1 0 2 2 Single attached
## 33 1 0 2 2 Single attached
## 34 1 0 2 2 Single attached
## 35 1 0 2 2 Single attached
## 36 1 0 2 2 Single attached
## 37 1 0 2 2 Single attached
## 38 1 0 2 2 Single attached
## 39 1 0 2 2 Single detached
## 40 1 0 2 2 Single detached
## 41 1 0 2 2 Single detached
## 42 1 0 2 2 Single detached
## 43 1 0 2 2 Single detached
## 44 1 0 2 2 Single detached
## 45 1 0 2 2 Single detached
## 46 1 0 2 3 Mobile home
## 47 1 0 2 3 Mobile home
## 48 1 0 2 3 Single attached
## 49 1 0 2 3 Single attached
## 50 1 0 2 3 Single attached
## 51 1 0 2 3 Single attached
## 52 1 0 2 3 Single attached
## 53 1 0 2 3 Single attached
## 54 1 0 2 3 Single attached
## 55 1 0 2 3 Single attached
## 56 1 0 2 3 Single detached
## 57 1 0 2 3 Single detached
## 58 1 0 2 3 Single detached
## 59 1 0 2 3 Single detached
## 60 1 0 2 3 Single detached
## 61 1 0 2 3 Single detached
## 62 1 0 2 3 Single detached
## 63 1 0 2 3 Single detached
## 64 1 0 2 3 Single detached
## 65 1 0 2 3 Single detached
## 66 1 0 2 3 Single detached
## 67 1 0 2 4 Single attached
## 68 1 0 2 4 Single attached
## 69 1 0 2 4 Single attached
## 70 1 0 2 4 Single attached
## 71 1 0 2 4 Single detached
## 72 1 0 2 4 Single detached
## 73 1 0 2 4 Single detached
## 74 1 0 2 4 Single detached
## 75 1 0 2 4 Single detached
## 76 1 0 2 4 Single detached
## 77 1 0 2 4 Single detached
## 78 1 0 2 4 Single detached
## 79 1 0 2 4 Single detached
## 80 1 0 2 4 Single detached
## 81 1 0 2 5 Mobile home
## 82 1 0 2 5 Mobile home
## 83 1 0 2 5 Mobile home
## 84 1 0 2 5 Single attached
## 85 1 0 2 5 Single attached
## 86 1 0 2 5 Single attached
## 87 1 0 2 5 Single detached
## 88 1 0 2 5 Single detached
## 89 1 0 2 5 Single detached
## 90 1 0 2 5 Single detached
## 91 1 0 2 5 Single detached
## 92 1 0 2 5 Single detached
## 93 1 0 2 5 Single detached
## 94 1 0 2 5 Single detached
## 95 1 0 2 6 Mobile home
## 96 1 0 2 6 Single attached
## 97 1 0 2 6 Single detached
## 98 1 0 2 6 Single detached
## 99 1 0 2 6 Single detached
## 100 1 0 2 6 Single detached
## 101 1 0 2 6 Single detached
## 102 1 0 2 6 Single detached
## 103 1 0 3 2 Single attached
## 104 1 0 3 2 Single detached
## 105 1 0 3 3 Single attached
## 106 1 0 3 3 Single attached
## 107 1 0 3 3 Single attached
## 108 1 0 3 3 Single detached
## 109 1 0 3 3 Single detached
## 110 1 0 3 4 Single attached
## 111 1 0 3 4 Single attached
## 112 1 0 3 4 Single detached
## 113 1 0 3 4 Single detached
## 114 1 0 3 5 Single attached
## 115 1 0 3 5 Single detached
## 116 1 0 3 5 Single detached
## 117 1 0 3 5 Single detached
## 118 1 0 3 6 Single attached
## 119 1 0 3 6 Single detached
## 120 1 0 3 6 Single detached
## 121 1 0 3 6 Single detached
## 122 1 0 4 2 Mobile home
## 123 1 0 4 2 Single attached
## 124 1 0 4 4 Single attached
## 125 1 0 4 6 Single detached
## 126 1 0 5 4 Single attached
## 127 1 0 5 5 Single detached
## 128 1 1 2 2 Single attached
## 129 1 1 2 2 Single attached
## 130 1 1 2 2 Single detached
## 131 1 1 2 3 Single attached
## 132 1 1 2 3 Single attached
## 133 1 1 2 3 Single detached
## 134 1 1 2 4 Mobile home
## 135 1 1 2 4 Single attached
## 136 1 1 2 4 Single detached
## 137 1 1 2 4 Single detached
## 138 1 1 3 2 Mobile home
## 139 1 1 3 2 Single attached
## 140 1 1 3 2 Single attached
## 141 1 1 3 2 Single detached
## 142 1 1 3 2 Single detached
## 143 1 1 3 3 Single attached
## 144 1 1 3 3 Single attached
## 145 1 1 3 3 Single detached
## 146 1 1 3 3 Single detached
## 147 1 1 3 3 Single detached
## 148 1 1 3 3 Single detached
## 149 1 1 3 3 Single detached
## 150 1 1 3 4 Single attached
## 151 1 1 3 4 Single detached
## 152 1 1 3 4 Single detached
## 153 1 1 3 4 Single detached
## 154 1 1 3 5 Mobile home
## 155 1 1 3 5 Single attached
## 156 1 1 3 5 Single attached
## 157 1 1 3 5 Single attached
## 158 1 1 3 5 Single detached
## 159 1 1 3 5 Single detached
## 160 1 1 3 6 Single attached
## 161 1 1 3 6 Single detached
## 162 1 1 3 6 Single detached
## 163 1 1 3 6 Single detached
## 164 1 1 4 2 Single detached
## 165 1 1 4 3 Single detached
## 166 1 1 4 4 Single detached
## 167 1 1 4 6 Single detached
## 168 1 2 3 3 Single attached
## 169 1 2 3 4 Single attached
## 170 1 2 4 2 Single attached
## 171 1 2 4 2 Single attached
## 172 1 2 4 2 Single detached
## 173 1 2 4 2 Single detached
## 174 1 2 4 3 Mobile home
## 175 1 2 4 3 Single attached
## 176 1 2 4 3 Single attached
## 177 1 2 4 3 Single detached
## 178 1 2 4 4 Single attached
## 179 1 2 4 4 Single attached
## 180 1 2 4 5 Single attached
## 181 1 2 4 5 Single detached
## 182 1 2 4 6 Single detached
## 183 1 2 5 2 Single attached
## 184 1 2 5 3 Single attached
## 185 1 2 5 6 Single attached
## 186 1 3 4 3 Single detached
## 187 1 3 5 3 Single detached
## 188 1 3 5 4 Single attached
## 189 1 3 5 4 Single detached
## 190 1 3 6 3 Single detached
## 191 1 5 7 4 Single attached
## 192 1 5 8 2 Single attached
## 193 2 0 2 3 Mobile home
## 194 2 0 2 3 Mobile home
## 195 2 0 2 3 Mobile home
## 196 2 0 2 3 Mobile home
## 197 2 0 2 3 Mobile home
## 198 2 0 2 3 Single attached
## 199 2 0 2 3 Single attached
## 200 2 0 2 3 Single attached
## 201 2 0 2 3 Single attached
## 202 2 0 2 3 Single attached
## 203 2 0 2 3 Single attached
## 204 2 0 2 3 Single attached
## 205 2 0 2 3 Single attached
## 206 2 0 2 3 Single detached
## 207 2 0 2 3 Single detached
## 208 2 0 2 3 Single detached
## 209 2 0 2 3 Single detached
## 210 2 0 2 3 Single detached
## 211 2 0 2 3 Single detached
## 212 2 0 2 3 Single detached
## 213 2 0 2 3 Single detached
## 214 2 0 2 3 Single detached
## 215 2 0 2 3 Single detached
## 216 2 0 2 3 Single detached
## 217 2 0 2 4 Mobile home
## 218 2 0 2 4 Mobile home
## 219 2 0 2 4 Mobile home
## 220 2 0 2 4 Mobile home
## 221 2 0 2 4 Mobile home
## 222 2 0 2 4 Mobile home
## 223 2 0 2 4 Mobile home
## 224 2 0 2 4 Mobile home
## 225 2 0 2 4 Mobile home
## 226 2 0 2 4 Single attached
## 227 2 0 2 4 Single attached
## 228 2 0 2 4 Single attached
## 229 2 0 2 4 Single attached
## 230 2 0 2 4 Single attached
## 231 2 0 2 4 Single attached
## 232 2 0 2 4 Single attached
## 233 2 0 2 4 Single attached
## 234 2 0 2 4 Single attached
## 235 2 0 2 4 Single detached
## 236 2 0 2 4 Single detached
## 237 2 0 2 4 Single detached
## 238 2 0 2 4 Single detached
## 239 2 0 2 4 Single detached
## 240 2 0 2 4 Single detached
## 241 2 0 2 4 Single detached
## 242 2 0 2 4 Single detached
## 243 2 0 2 4 Single detached
## 244 2 0 2 4 Single detached
## 245 2 0 2 4 Single detached
## 246 2 0 2 4 Single detached
## 247 2 0 2 4 Single detached
## 248 2 0 2 4 Single detached
## 249 2 0 2 4 Single detached
## 250 2 0 2 5 Mobile home
## 251 2 0 2 5 Mobile home
## 252 2 0 2 5 Mobile home
## 253 2 0 2 5 Mobile home
## 254 2 0 2 5 Mobile home
## 255 2 0 2 5 Mobile home
## 256 2 0 2 5 Mobile home
## 257 2 0 2 5 Mobile home
## 258 2 0 2 5 Single attached
## 259 2 0 2 5 Single attached
## 260 2 0 2 5 Single attached
## 261 2 0 2 5 Single attached
## 262 2 0 2 5 Single attached
## 263 2 0 2 5 Single attached
## 264 2 0 2 5 Single attached
## 265 2 0 2 5 Single attached
## 266 2 0 2 5 Single attached
## 267 2 0 2 5 Single attached
## 268 2 0 2 5 Single attached
## 269 2 0 2 5 Single detached
## 270 2 0 2 5 Single detached
## 271 2 0 2 5 Single detached
## 272 2 0 2 5 Single detached
## 273 2 0 2 5 Single detached
## 274 2 0 2 5 Single detached
## 275 2 0 2 5 Single detached
## 276 2 0 2 5 Single detached
## 277 2 0 2 5 Single detached
## 278 2 0 2 5 Single detached
## 279 2 0 2 5 Single detached
## 280 2 0 2 5 Single detached
## 281 2 0 2 5 Single detached
## 282 2 0 2 5 Single detached
## 283 2 0 2 5 Single detached
## 284 2 0 2 6 Mobile home
## 285 2 0 2 6 Mobile home
## 286 2 0 2 6 Mobile home
## 287 2 0 2 6 Mobile home
## 288 2 0 2 6 Mobile home
## 289 2 0 2 6 Mobile home
## 290 2 0 2 6 Single attached
## 291 2 0 2 6 Single attached
## 292 2 0 2 6 Single attached
## 293 2 0 2 6 Single attached
## 294 2 0 2 6 Single attached
## 295 2 0 2 6 Single attached
## 296 2 0 2 6 Single attached
## 297 2 0 2 6 Single attached
## 298 2 0 2 6 Single attached
## 299 2 0 2 6 Single detached
## 300 2 0 2 6 Single detached
## 301 2 0 2 6 Single detached
## 302 2 0 2 6 Single detached
## 303 2 0 2 6 Single detached
## 304 2 0 2 6 Single detached
## 305 2 0 2 6 Single detached
## 306 2 0 2 6 Single detached
## 307 2 0 2 6 Single detached
## 308 2 0 2 6 Single detached
## 309 2 0 2 6 Single detached
## 310 2 0 2 6 Single detached
## 311 2 0 2 6 Single detached
## 312 2 0 2 6 Single detached
## 313 2 0 2 6 Single detached
## 314 2 0 2 7 Mobile home
## 315 2 0 2 7 Mobile home
## 316 2 0 2 7 Single attached
## 317 2 0 2 7 Single attached
## 318 2 0 2 7 Single attached
## 319 2 0 2 7 Single attached
## 320 2 0 2 7 Single attached
## 321 2 0 2 7 Single attached
## 322 2 0 2 7 Single attached
## 323 2 0 2 7 Single attached
## 324 2 0 2 7 Single detached
## 325 2 0 2 7 Single detached
## 326 2 0 2 7 Single detached
## 327 2 0 2 7 Single detached
## 328 2 0 2 7 Single detached
## 329 2 0 2 7 Single detached
## 330 2 0 2 7 Single detached
## 331 2 0 2 7 Single detached
## 332 2 0 2 7 Single detached
## 333 2 0 2 7 Single detached
## 334 2 0 2 7 Single detached
## 335 2 0 2 7 Single detached
## 336 2 0 2 7 Single detached
## 337 2 0 2 7 Single detached
## 338 2 0 2 8 Single attached
## 339 2 0 2 8 Single attached
## 340 2 0 2 8 Single attached
## 341 2 0 2 8 Single attached
## 342 2 0 2 8 Single attached
## 343 2 0 2 8 Single attached
## 344 2 0 2 8 Single attached
## 345 2 0 2 8 Single attached
## 346 2 0 2 8 Single detached
## 347 2 0 2 8 Single detached
## 348 2 0 2 8 Single detached
## 349 2 0 2 8 Single detached
## 350 2 0 2 8 Single detached
## 351 2 0 2 8 Single detached
## 352 2 0 2 8 Single detached
## 353 2 0 2 8 Single detached
## 354 2 0 2 8 Single detached
## 355 2 0 2 9 Single attached
## 356 2 0 2 9 Single attached
## 357 2 0 2 9 Single detached
## 358 2 0 2 9 Single detached
## 359 2 0 2 9 Single detached
## 360 2 0 2 9 Single detached
## 361 2 0 2 9 Single detached
## 362 2 0 2 9 Single detached
## 363 2 0 2 9 Single detached
## 364 2 0 2 9 Single detached
## 365 2 0 2 9 Single detached
## 366 2 0 2 10 Single detached
## 367 2 0 2 10 Single detached
## 368 2 0 2 10 Single detached
## 369 2 0 2 10 Single detached
## 370 2 0 2 10 Single detached
## 371 2 0 2 10 Single detached
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## 5608 8 4 8 21 Single detached
## 5609 8 4 9 11 Single attached
## 5610 8 4 12 11 Single detached
## 5611 8 4 13 8 Single detached
## 5612 8 5 7 9 Single detached
## 5613 8 5 7 9 Single detached
## 5614 8 5 7 10 Single detached
## 5615 8 5 7 10 Single detached
## 5616 8 5 7 11 Single detached
## 5617 8 5 7 11 Single detached
## 5618 8 5 7 12 Single attached
## 5619 8 5 7 12 Single detached
## 5620 8 5 7 12 Single detached
## 5621 8 5 7 13 Single detached
## 5622 8 5 7 13 Single detached
## 5623 8 5 7 21 Single detached
## 5624 8 5 9 9 Single detached
## 5625 8 5 9 11 Single detached
## 5626 8 5 10 11 Single detached
## 5627 8 5 10 11 Single detached
## 5628 8 5 10 11 Single detached
## 5629 8 5 12 11 Single detached
## 5630 8 6 8 9 Single detached
## 5631 8 6 8 10 Single detached
## 5632 8 6 8 12 Single detached
## 5633 8 6 8 12 Single detached
## 5634 8 6 8 13 Single detached
## 5635 8 7 9 8 Single detached
## 5636 8 7 10 10 Single detached
## 5637 8 7 10 10 Single detached
## 5638 8 8 10 9 Single detached
## 5639 8 8 10 9 Single detached
## 5640 8 8 10 10 Single detached
## 5641 8 8 10 11 Single detached
## 5642 8 10 12 9 Single detached
## 5643 8 12 15 21 Single detached
## NumVehicles NumWorkers mean_income
## 1 0 1 18200.000
## 2 1 2 24650.000
## 3 2 0 13600.000
## 4 2 2 128200.000
## 5 3 2 120100.000
## 6 4 2 86800.000
## 7 1 1 12000.000
## 8 1 2 21400.000
## 9 1 0 14900.000
## 10 2 3 122870.000
## 11 1 2 74150.000
## 12 2 2 96300.000
## 13 1 3 147000.000
## 14 2 2 40000.000
## 15 0 1 30700.000
## 16 2 2 74000.000
## 17 0 0 410.000
## 18 2 2 129000.000
## 19 3 2 154000.000
## 20 4 2 91500.000
## 21 2 1 18800.000
## 22 2 2 163333.333
## 23 3 2 73000.000
## 24 3 2 71100.000
## 25 2 2 41050.000
## 26 3 3 136650.000
## 27 0 0 480.000
## 28 2 2 47510.000
## 29 1 2 29000.000
## 30 2 2 44500.000
## 31 0 0 14956.667
## 32 0 1 54500.000
## 33 0 2 54650.000
## 34 1 1 41200.000
## 35 1 2 78166.667
## 36 2 1 64400.000
## 37 2 2 129000.000
## 38 6 1 110000.000
## 39 0 1 12000.000
## 40 0 2 40370.000
## 41 1 0 82300.000
## 42 1 1 34500.000
## 43 1 2 23000.000
## 44 2 1 47200.000
## 45 2 2 60486.667
## 46 1 1 87550.000
## 47 3 1 40000.000
## 48 0 0 51550.000
## 49 0 1 32792.000
## 50 1 0 40250.000
## 51 1 1 46886.000
## 52 1 2 48000.000
## 53 2 0 39900.000
## 54 2 1 78978.000
## 55 2 2 161560.000
## 56 0 0 16625.000
## 57 0 1 22200.000
## 58 0 2 33500.000
## 59 1 0 17000.000
## 60 1 1 49453.333
## 61 1 2 85600.000
## 62 2 1 76401.818
## 63 2 2 72313.333
## 64 3 1 79750.000
## 65 3 2 85000.000
## 66 4 2 77700.000
## 67 1 0 44050.000
## 68 1 1 81850.000
## 69 1 2 53566.667
## 70 2 1 117500.000
## 71 0 0 13600.000
## 72 0 1 21386.667
## 73 0 2 39300.000
## 74 1 0 26500.000
## 75 1 2 60700.000
## 76 2 0 54300.000
## 77 2 1 79178.462
## 78 2 2 78685.556
## 79 3 2 95764.000
## 80 4 1 50000.000
## 81 1 1 44600.000
## 82 2 0 38700.000
## 83 2 2 90500.000
## 84 1 1 87900.000
## 85 2 0 18600.000
## 86 2 2 121000.000
## 87 0 2 38605.000
## 88 1 0 46300.000
## 89 1 1 42052.500
## 90 1 2 37400.000
## 91 2 0 35645.000
## 92 2 1 49175.000
## 93 2 2 70700.000
## 94 3 0 58200.000
## 95 2 0 9900.000
## 96 2 2 202590.000
## 97 1 2 90300.000
## 98 2 0 33210.000
## 99 2 1 57633.333
## 100 2 2 71314.400
## 101 3 2 55500.000
## 102 4 2 146000.000
## 103 1 2 36000.000
## 104 0 2 23090.000
## 105 0 1 44400.000
## 106 2 1 151400.000
## 107 3 3 83200.000
## 108 1 2 10880.000
## 109 2 2 62000.000
## 110 0 1 12790.000
## 111 1 2 114000.000
## 112 0 2 71000.000
## 113 3 3 81000.000
## 114 2 3 139800.000
## 115 0 0 23800.000
## 116 3 1 58300.000
## 117 3 3 96000.000
## 118 2 2 160000.000
## 119 2 1 37700.000
## 120 2 3 48000.000
## 121 4 3 101800.000
## 122 1 3 28050.000
## 123 0 3 45200.000
## 124 2 0 25100.000
## 125 2 0 26300.000
## 126 3 3 54100.000
## 127 3 3 65700.000
## 128 0 1 16800.000
## 129 1 1 47400.000
## 130 1 1 66000.000
## 131 0 1 11400.000
## 132 1 1 11400.000
## 133 1 1 2100.000
## 134 1 1 21000.000
## 135 1 1 32000.000
## 136 0 1 15010.000
## 137 1 1 27100.000
## 138 1 1 13600.000
## 139 1 1 49400.000
## 140 1 2 101000.000
## 141 1 1 25000.000
## 142 1 2 19500.000
## 143 0 1 14050.000
## 144 2 2 115000.000
## 145 1 1 37666.667
## 146 1 2 46000.000
## 147 2 1 70000.000
## 148 2 2 100650.000
## 149 3 1 42000.000
## 150 1 2 118200.000
## 151 0 1 20000.000
## 152 1 2 22950.000
## 153 2 1 30300.000
## 154 2 1 27700.000
## 155 0 2 61000.000
## 156 1 1 170000.000
## 157 1 2 49800.000
## 158 3 2 118000.000
## 159 4 2 120000.000
## 160 2 2 130000.000
## 161 0 1 3400.000
## 162 1 1 10000.000
## 163 2 1 30000.000
## 164 0 2 17600.000
## 165 0 1 18200.000
## 166 2 2 100000.000
## 167 3 2 52200.000
## 168 2 1 32700.000
## 169 1 1 40000.000
## 170 0 2 44400.000
## 171 1 2 122000.000
## 172 0 2 31200.000
## 173 3 0 13200.000
## 174 1 0 8400.000
## 175 0 1 65000.000
## 176 1 1 104000.000
## 177 1 2 104000.000
## 178 0 3 69500.000
## 179 1 2 41700.000
## 180 0 2 43640.000
## 181 1 2 98000.000
## 182 3 1 100000.000
## 183 1 1 13000.000
## 184 0 1 26000.000
## 185 0 2 130000.000
## 186 1 1 18000.000
## 187 0 1 35333.333
## 188 0 1 10000.000
## 189 2 2 100000.000
## 190 1 2 42600.000
## 191 1 1 100000.000
## 192 0 1 1400.000
## 193 1 1 45000.000
## 194 1 2 41166.667
## 195 2 0 52700.000
## 196 2 1 40750.000
## 197 2 2 70000.000
## 198 0 1 17300.000
## 199 0 2 24500.000
## 200 1 1 29250.000
## 201 1 2 53500.000
## 202 2 0 23700.000
## 203 2 1 70900.000
## 204 2 2 237350.000
## 205 3 0 111900.000
## 206 0 2 73550.000
## 207 1 0 17000.000
## 208 1 1 64060.000
## 209 1 2 39500.000
## 210 2 0 20500.000
## 211 2 1 50651.250
## 212 2 2 96573.077
## 213 3 0 96200.000
## 214 3 1 28000.000
## 215 3 2 79540.000
## 216 4 2 95000.000
## 217 0 0 10500.000
## 218 1 0 22919.091
## 219 1 1 30545.000
## 220 1 2 52000.000
## 221 2 0 35075.000
## 222 2 1 40981.818
## 223 2 2 55345.455
## 224 3 1 27533.333
## 225 3 2 76000.000
## 226 0 0 33500.000
## 227 0 1 34803.333
## 228 0 2 54933.333
## 229 1 0 59703.333
## 230 1 1 49316.923
## 231 1 2 89383.636
## 232 2 0 78618.333
## 233 2 1 72341.538
## 234 2 2 123247.407
## 235 0 0 23350.000
## 236 0 1 49775.000
## 237 0 2 46620.000
## 238 1 0 34866.250
## 239 1 1 58447.619
## 240 1 2 93053.944
## 241 2 0 51914.545
## 242 2 1 65648.056
## 243 2 2 85163.457
## 244 3 0 28400.000
## 245 3 1 65375.000
## 246 3 2 90601.875
## 247 4 0 71300.000
## 248 4 1 39600.000
## 249 4 2 106500.000
## 250 0 0 9500.000
## 251 0 2 35000.000
## 252 1 0 23000.000
## 253 1 1 40060.000
## 254 1 2 57150.000
## 255 2 0 33566.667
## 256 2 1 40784.286
## 257 2 2 40828.571
## 258 0 0 29992.000
## 259 0 1 43640.000
## 260 1 0 40728.889
## 261 1 1 57846.250
## 262 1 2 85353.846
## 263 2 0 81496.000
## 264 2 1 58739.333
## 265 2 2 120062.077
## 266 3 0 96000.000
## 267 3 1 116333.333
## 268 3 2 189000.000
## 269 0 0 16180.000
## 270 0 1 19033.333
## 271 0 2 81920.000
## 272 1 0 35648.212
## 273 1 1 44810.645
## 274 1 2 75065.333
## 275 2 0 56215.172
## 276 2 1 71378.852
## 277 2 2 91428.015
## 278 3 0 34550.000
## 279 3 1 133780.000
## 280 3 2 90820.833
## 281 4 0 45500.000
## 282 4 1 76550.000
## 283 4 2 81405.000
## 284 1 0 38400.000
## 285 1 1 34970.000
## 286 2 0 20900.000
## 287 2 1 42675.000
## 288 2 2 44866.667
## 289 4 1 56000.000
## 290 0 0 22333.333
## 291 0 1 49150.000
## 292 0 2 43300.000
## 293 1 0 39240.000
## 294 1 1 49582.857
## 295 1 2 64785.000
## 296 2 0 122180.000
## 297 2 1 129271.429
## 298 2 2 149086.364
## 299 0 0 49800.000
## 300 0 1 35000.000
## 301 0 2 57266.667
## 302 1 0 44169.167
## 303 1 1 61014.952
## 304 1 2 69036.429
## 305 2 0 46886.522
## 306 2 1 66225.907
## 307 2 2 95725.507
## 308 3 0 96800.000
## 309 3 1 68300.000
## 310 3 2 154348.667
## 311 4 1 125000.000
## 312 4 2 196840.000
## 313 6 1 55600.000
## 314 1 1 46275.000
## 315 2 1 30500.000
## 316 0 1 15100.000
## 317 1 0 70400.000
## 318 1 1 84000.000
## 319 1 2 42000.000
## 320 2 0 83200.000
## 321 2 1 203470.000
## 322 2 2 129545.000
## 323 3 2 98000.000
## 324 0 0 11000.000
## 325 0 1 18100.000
## 326 0 2 77500.000
## 327 1 0 48162.500
## 328 1 1 52166.667
## 329 1 2 87800.000
## 330 2 0 62783.333
## 331 2 1 82347.222
## 332 2 2 93387.907
## 333 3 0 63433.333
## 334 3 1 614800.000
## 335 3 2 125983.333
## 336 4 1 150000.000
## 337 4 2 50850.000
## 338 0 0 31000.000
## 339 0 1 95800.000
## 340 0 2 108350.000
## 341 1 1 336000.000
## 342 2 0 127600.000
## 343 2 1 121150.000
## 344 2 2 80312.500
## 345 3 2 87000.000
## 346 1 0 58626.000
## 347 1 1 88027.500
## 348 1 2 68000.000
## 349 2 0 77305.000
## 350 2 1 65923.889
## 351 2 2 106546.667
## 352 3 1 56250.000
## 353 3 2 82166.667
## 354 4 2 76300.000
## 355 2 1 293000.000
## 356 2 2 198000.000
## 357 0 1 47100.000
## 358 1 0 24400.000
## 359 1 2 116100.000
## 360 2 0 43400.000
## 361 2 1 83500.000
## 362 2 2 74644.444
## 363 3 1 55120.000
## 364 3 2 61500.000
## 365 4 2 178000.000
## 366 1 0 22300.000
## 367 1 1 35800.000
## 368 2 0 71400.000
## 369 2 2 77866.667
## 370 3 0 46800.000
## 371 3 1 80900.000
## 372 3 2 153000.000
## 373 4 0 57500.000
## 374 4 2 67000.000
## 375 2 1 44800.000
## 376 2 2 71950.000
## 377 3 1 88000.000
## 378 2 1 33300.000
## 379 1 1 14400.000
## 380 1 2 90000.000
## 381 2 1 55750.000
## 382 2 3 94900.000
## 383 0 1 15280.000
## 384 1 0 28300.000
## 385 1 1 170700.000
## 386 1 2 52350.000
## 387 1 3 50021.000
## 388 2 1 40100.000
## 389 2 2 33100.000
## 390 4 2 148200.000
## 391 2 2 46300.000
## 392 3 2 57710.000
## 393 4 1 45200.000
## 394 0 1 68400.000
## 395 0 2 50000.000
## 396 1 0 23860.000
## 397 1 1 38757.500
## 398 1 2 70750.000
## 399 1 3 77285.000
## 400 2 0 14900.000
## 401 2 2 29000.000
## 402 3 1 144400.000
## 403 3 3 206950.000
## 404 0 1 67833.333
## 405 0 2 30950.000
## 406 0 3 61900.000
## 407 1 0 16000.000
## 408 1 1 38733.333
## 409 1 2 48350.000
## 410 1 3 57633.333
## 411 2 0 66000.000
## 412 2 1 36000.000
## 413 2 2 80278.750
## 414 2 3 118450.000
## 415 3 0 64200.000
## 416 3 1 45874.000
## 417 3 2 79600.000
## 418 3 3 90700.000
## 419 4 2 53500.000
## 420 4 3 90000.000
## 421 6 3 138000.000
## 422 0 1 10000.000
## 423 1 1 9800.000
## 424 0 2 72725.000
## 425 0 3 74900.000
## 426 1 1 81874.000
## 427 1 2 102083.333
## 428 1 3 74000.000
## 429 2 0 46500.000
## 430 2 1 112700.000
## 431 2 3 83933.333
## 432 3 2 110400.000
## 433 3 3 158350.000
## 434 0 2 13000.000
## 435 0 3 63400.000
## 436 1 1 26100.000
## 437 1 2 56633.333
## 438 1 3 139050.000
## 439 2 0 34100.000
## 440 2 1 52780.000
## 441 2 2 60311.429
## 442 2 3 87530.000
## 443 3 1 56564.000
## 444 3 2 73133.333
## 445 3 3 92707.273
## 446 4 1 20400.000
## 447 4 3 29300.000
## 448 1 1 22700.000
## 449 2 1 92430.000
## 450 1 0 68350.000
## 451 1 2 60500.000
## 452 2 1 127900.000
## 453 2 3 80700.000
## 454 3 1 52000.000
## 455 3 2 394150.000
## 456 3 3 190000.000
## 457 0 1 75200.000
## 458 1 0 14200.000
## 459 1 1 51700.000
## 460 1 2 74500.000
## 461 1 3 72900.000
## 462 2 0 59000.000
## 463 2 1 77820.000
## 464 2 2 139412.500
## 465 2 3 237900.000
## 466 3 1 81900.000
## 467 3 2 96672.857
## 468 3 3 104478.750
## 469 4 1 70200.000
## 470 4 2 46800.000
## 471 4 3 91250.000
## 472 1 2 112000.000
## 473 2 2 111200.000
## 474 3 2 79700.000
## 475 1 1 87550.000
## 476 1 2 44600.000
## 477 2 1 84600.000
## 478 2 3 201000.000
## 479 3 1 58200.000
## 480 3 2 81871.429
## 481 3 3 90340.000
## 482 4 3 97430.000
## 483 1 1 106800.000
## 484 1 3 58300.000
## 485 2 1 115100.000
## 486 2 2 98470.000
## 487 2 3 85466.667
## 488 3 0 26000.000
## 489 3 3 137166.667
## 490 5 1 110800.000
## 491 3 2 117000.000
## 492 2 3 85000.000
## 493 6 2 127060.000
## 494 2 0 29900.000
## 495 3 1 31200.000
## 496 3 2 23960.000
## 497 2 1 93700.000
## 498 5 3 204000.000
## 499 1 1 35200.000
## 500 1 2 98800.000
## 501 2 2 97600.000
## 502 3 3 120000.000
## 503 4 3 135000.000
## 504 1 3 46850.000
## 505 0 1 40500.000
## 506 0 2 24000.000
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## 509 1 2 76150.000
## 510 2 2 89700.000
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## 512 1 0 15500.000
## 513 1 2 152140.000
## 514 1 3 46000.000
## 515 2 1 16400.000
## 516 2 2 71900.000
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## 518 3 2 191300.000
## 519 3 3 77515.000
## 520 4 3 63100.000
## 521 5 3 180400.000
## 522 1 2 85000.000
## 523 2 2 46500.000
## 524 0 3 50300.000
## 525 1 1 49700.000
## 526 1 3 136500.000
## 527 2 2 102400.000
## 528 2 3 112800.000
## 529 1 1 49000.000
## 530 1 2 105900.000
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## 532 2 3 124000.000
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## 534 4 3 133252.500
## 535 1 1 91400.000
## 536 1 3 135875.000
## 537 3 3 113600.000
## 538 4 2 110000.000
## 539 1 1 41700.000
## 540 1 2 97300.000
## 541 2 3 107500.000
## 542 3 2 314600.000
## 543 3 3 85000.000
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## 545 5 3 212400.000
## 546 2 3 28500.000
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## 555 0 0 55300.000
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## 558 0 1 27000.000
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## 562 0 3 198300.000
## 563 1 3 117000.000
## 564 2 1 22000.000
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## 569 1 0 70600.000
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## 580 0 3 10270.000
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## 590 1 0 8600.000
## 591 1 1 18014.286
## 592 2 1 25000.000
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## 603 0 0 12430.000
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## 5643 2 3 81600.000ddply(acs_fit,.(OwnRent), summarise, mean_income=mean(FamilyIncome))## OwnRent mean_income
## 1 Mortgage 117551.80
## 2 Outright 109695.55
## 3 Rented 55771.63Count (family income) by various important indicators/variables
# Family Type
tapply(acs_fit$FamilyIncome,acs_fit$FamilyType,length)## Female Head Male Head Married
## 2594 907 14695tapply(acs_fit$FamilyIncome,acs_fit$FamilyType,mean)## Female Head Male Head Married
## 60242.74 72992.65 121966.88# Own/Rent
tapply(acs_fit$FamilyIncome,acs_fit$OwnRent,length)## Mortgage Outright Rented
## 16074 128 1994tapply(acs_fit$FamilyIncome,acs_fit$OwnRent,mean)## Mortgage Outright Rented
## 117551.80 109695.55 55771.63# Insurance
tapply(acs_fit$FamilyIncome,acs_fit$FoodStamp,length)## No Yes
## 16777 1419tapply(acs_fit$FamilyIncome,acs_fit$FoodStamp,mean)## No Yes
## 115898.77 49572.72Task 3 - Building predictive classifier models using the entire training dataset
Let’s start by building a null model in which you simply predict that everyone’s income is < 250000 (since the majority of incomes are less than 250000).
acs$null_model <- 0Create a confusion matrix table and compute the overall accuracy of this model as well as its sensitivity and specificity.
library(caret)
table(acs$HighIncome, acs$null_model)##
## 0
## 0 21356
## 1 1389prop.table(table(acs$HighIncome, acs$null_model))##
## 0
## 0 0.93893163
## 1 0.06106837confusionMatrix(as.factor(acs$null_model), as.factor(acs$HighIncome), positive = "1")## Warning in confusionMatrix.default(as.factor(acs$null_model), as.factor(acs
## $HighIncome), : Levels are not in the same order for reference and data.
## Refactoring data to match.## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 21356 1389
## 1 0 0
##
## Accuracy : 0.9389
## 95% CI : (0.9357, 0.942)
## No Information Rate : 0.9389
## P-Value [Acc > NIR] : 0.5071
##
## Kappa : 0
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.00000
## Specificity : 1.00000
## Pos Pred Value : NaN
## Neg Pred Value : 0.93893
## Prevalence : 0.06107
## Detection Rate : 0.00000
## Detection Prevalence : 0.00000
## Balanced Accuracy : 0.50000
##
## 'Positive' Class : 1
## We would like to build a more accurate model than this. Your job is to build classifiers to predict the binary HighIncome we created. You will be using three different classification techniques: * decision trees (use rpart package - see Kaggle Titanic example from StatModels2 or session on trees) * logistic regression (see logistic regression examples we did in StatModels2) * k-nearest neighbor or some other technique (see kNN example we did in StatModels2) For each technique, you should: * build a few models with the training data * create confusion matrices (using caret package) to pick the best fit model for each technique * use your three best fit models (one from each technique) to predict using the test dataset and evaluate which of the models performs the best * write a few paragraphs discussing what you did and what you found. In particular, how difficult is it to predict HighIncome? Did one of the techniques outperform the other two?
Logistic Regression
- specify the model
- show summary results
- check fitted values from the model
- set variable equal to fitted values with probability greater than 50%
- show fitted values for visual check of model
- confusion matrix
logistic regression model 1
logmod1 <- glm(HighIncome ~ FamilyType + NumVehicles + OwnRent + Insurance + YearBuilt, data=acs_fit, family=binomial(link="logit"))
summary(logmod1)##
## Call:
## glm(formula = HighIncome ~ FamilyType + NumVehicles + OwnRent +
## Insurance + YearBuilt, family = binomial(link = "logit"),
## data = acs_fit)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.9844 -0.3540 -0.2875 -0.1979 3.3452
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.606e+01 1.539e+02 -0.104 0.917
## FamilyTypeMale Head 6.722e-01 3.116e-01 2.157 0.031 *
## FamilyTypeMarried 1.674e+00 2.035e-01 8.225 < 2e-16 ***
## NumVehicles 2.463e-01 3.374e-02 7.300 2.88e-13 ***
## OwnRentOutright 7.038e-01 3.182e-01 2.212 0.027 *
## OwnRentRented -1.159e-01 1.937e-01 -0.598 0.550
## Insurance 6.605e-04 2.212e-05 29.855 < 2e-16 ***
## YearBuilt1940-1949 9.780e+00 1.539e+02 0.064 0.949
## YearBuilt1950-1959 1.034e+01 1.539e+02 0.067 0.946
## YearBuilt1960-1969 1.036e+01 1.539e+02 0.067 0.946
## YearBuilt1970-1979 1.015e+01 1.539e+02 0.066 0.947
## YearBuilt1980-1989 1.049e+01 1.539e+02 0.068 0.946
## YearBuilt1990-1999 1.050e+01 1.539e+02 0.068 0.946
## YearBuilt2000-2004 1.061e+01 1.539e+02 0.069 0.945
## YearBuilt2005 1.071e+01 1.539e+02 0.070 0.945
## YearBuilt2006 1.105e+01 1.539e+02 0.072 0.943
## YearBuilt2007 1.074e+01 1.539e+02 0.070 0.944
## YearBuilt2008 1.080e+01 1.539e+02 0.070 0.944
## YearBuilt2009 1.046e+01 1.539e+02 0.068 0.946
## YearBuilt2010 1.135e+01 1.539e+02 0.074 0.941
## YearBuiltBefore 1939 1.033e+01 1.539e+02 0.067 0.946
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8398.1 on 18195 degrees of freedom
## Residual deviance: 7076.0 on 18175 degrees of freedom
## AIC: 7118
##
## Number of Fisher Scoring iterations: 12#logmod1$fitted.values[1:10] - use this to check probabilities
yhat_logmod1 <- (logmod1$fitted.values > 0.05) * 1
#logmod1$y[1:200] - use this to check fitted values
summary(as.factor(yhat_logmod1))## 0 1
## 10666 7530summary(logmod1$fitted.values)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000001 0.0251500 0.0438900 0.0613900 0.0667100 0.8604000log_cm1 <- confusionMatrix(as.factor(yhat_logmod1), as.factor(acs_fit$HighIncome), positive = "1")
log_cm1## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 10458 208
## 1 6621 909
##
## Accuracy : 0.6247
## 95% CI : (0.6176, 0.6317)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.1157
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.81379
## Specificity : 0.61233
## Pos Pred Value : 0.12072
## Neg Pred Value : 0.98050
## Prevalence : 0.06139
## Detection Rate : 0.04996
## Detection Prevalence : 0.41383
## Balanced Accuracy : 0.71306
##
## 'Positive' Class : 1
## logistic regression model 2
logmod2 <- glm(HighIncome ~ FamilyType + FoodStamp + OwnRent, data=acs_fit, family=binomial(link="logit"))
summary(logmod2)##
## Call:
## glm(formula = HighIncome ~ FamilyType + FoodStamp + OwnRent,
## family = binomial(link = "logit"), data = acs_fit)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.4992 -0.4048 -0.4048 -0.1728 3.7799
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.1971 0.1947 -21.557 < 2e-16 ***
## FamilyTypeMale Head 0.6399 0.3026 2.114 0.0345 *
## FamilyTypeMarried 1.7363 0.1968 8.821 < 2e-16 ***
## FoodStampYes -1.9012 0.3578 -5.314 1.08e-07 ***
## OwnRentOutright 0.4413 0.2964 1.489 0.1365
## OwnRentRented -1.0447 0.1885 -5.541 3.00e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8398.1 on 18195 degrees of freedom
## Residual deviance: 8037.1 on 18190 degrees of freedom
## AIC: 8049.1
##
## Number of Fisher Scoring iterations: 7#logmod2$fitted.values[1:10] - use this to check probabilities
yhat_logmod2 <- (logmod2$fitted.values > 0.5) * 1
#logmod2$y[1:50] - use this to check fitted values
log_cm2 <- confusionMatrix(as.factor(yhat_logmod2), as.factor(acs_fit$HighIncome), positive = "1")## Warning in confusionMatrix.default(as.factor(yhat_logmod2),
## as.factor(acs_fit$HighIncome), : Levels are not in the same order for
## reference and data. Refactoring data to match.log_cm2## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 17079 1117
## 1 0 0
##
## Accuracy : 0.9386
## 95% CI : (0.935, 0.9421)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.508
##
## Kappa : 0
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.00000
## Specificity : 1.00000
## Pos Pred Value : NaN
## Neg Pred Value : 0.93861
## Prevalence : 0.06139
## Detection Rate : 0.00000
## Detection Prevalence : 0.00000
## Balanced Accuracy : 0.50000
##
## 'Positive' Class : 1
## logistic regression model 3
logmod3 <- glm(HighIncome ~ InsuranceHigh + NumWorkers2 + HouseCostsHigh + FoodStamp + OwnRent, data=acs_fit, family=binomial(link="logit"))
summary(logmod3)##
## Call:
## glm(formula = HighIncome ~ InsuranceHigh + NumWorkers2 + HouseCostsHigh +
## FoodStamp + OwnRent, family = binomial(link = "logit"), data = acs_fit)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.2253 -0.3183 -0.2682 -0.1640 3.6467
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.30241 0.09797 -43.915 < 2e-16 ***
## InsuranceHigh 1.34537 0.07504 17.929 < 2e-16 ***
## NumWorkers2 0.07590 0.06409 1.184 0.2363
## HouseCostsHigh 1.26356 0.09694 13.035 < 2e-16 ***
## FoodStampYes -2.07741 0.35866 -5.792 6.95e-09 ***
## OwnRentOutright 1.72956 0.31359 5.515 3.48e-08 ***
## OwnRentRented -0.34415 0.19554 -1.760 0.0784 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8398.1 on 18195 degrees of freedom
## Residual deviance: 7305.5 on 18189 degrees of freedom
## AIC: 7319.5
##
## Number of Fisher Scoring iterations: 7#logmod3$fit[18100:18196] - use this to check probabilities
yhat_logmod3 <- (logmod3$fit > 0.5) * 1
#logmod3$y[18000:18196] - use this to check fitted values
log_cm3 <- confusionMatrix(as.factor(yhat_logmod3), as.factor(acs_fit$HighIncome), positive = "1")
log_cm3## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 17078 1117
## 1 1 0
##
## Accuracy : 0.9386
## 95% CI : (0.935, 0.942)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.5203
##
## Kappa : -1e-04
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.000e+00
## Specificity : 9.999e-01
## Pos Pred Value : 0.000e+00
## Neg Pred Value : 9.386e-01
## Prevalence : 6.139e-02
## Detection Rate : 0.000e+00
## Detection Prevalence : 5.496e-05
## Balanced Accuracy : 5.000e-01
##
## 'Positive' Class : 1
## logistic regression model 4
logmod4 <- glm(HighIncome ~ InsuranceHigh + NumWorkers2 + HouseCostsHigh, data=acs_fit, family=binomial(link="logit"))
summary(logmod4)##
## Call:
## glm(formula = HighIncome ~ InsuranceHigh + NumWorkers2 + HouseCostsHigh,
## family = binomial(link = "logit"), data = acs_fit)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.5958 -0.3163 -0.2879 -0.1577 2.9642
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.38071 0.09202 -47.604 <2e-16 ***
## InsuranceHigh 1.41041 0.07252 19.447 <2e-16 ***
## NumWorkers2 0.11334 0.06374 1.778 0.0753 .
## HouseCostsHigh 1.21827 0.09407 12.950 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8398.1 on 18195 degrees of freedom
## Residual deviance: 7404.8 on 18192 degrees of freedom
## AIC: 7412.8
##
## Number of Fisher Scoring iterations: 6#logmod4$fit[18100:18196] - use this to check probabilities
yhat_logmod4 <- (logmod4$fit > 0.5) * 1
#logmod4$y[18000:18196] - use this to check fitted values
log_cm4 <- confusionMatrix(as.factor(yhat_logmod4), as.factor(acs_fit$HighIncome), positive = "1")## Warning in confusionMatrix.default(as.factor(yhat_logmod4),
## as.factor(acs_fit$HighIncome), : Levels are not in the same order for
## reference and data. Refactoring data to match.logistic regression model 5
logmod5 <- glm(HighIncome ~ HouseCostsHigh, data=acs_fit, family=binomial(link="logit"))
summary(logmod5)##
## Call:
## glm(formula = HighIncome ~ HouseCostsHigh, family = binomial(link = "logit"),
## data = acs_fit)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.4537 -0.4537 -0.1909 -0.1909 2.8336
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.99649 0.08239 -48.51 <2e-16 ***
## HouseCostsHigh 1.77486 0.08907 19.93 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 8398.1 on 18195 degrees of freedom
## Residual deviance: 7833.6 on 18194 degrees of freedom
## AIC: 7837.6
##
## Number of Fisher Scoring iterations: 6#logmod5$fit[18100:18196] - use this to check probabilities
yhat_logmod5 <- (logmod4$fit > 0.5) * 1
#logmod5$y[18000:18196] - use this to check fitted values
log_cm5 <- confusionMatrix(as.factor(yhat_logmod5), as.factor(acs_fit$HighIncome), positive = "1")## Warning in confusionMatrix.default(as.factor(yhat_logmod5),
## as.factor(acs_fit$HighIncome), : Levels are not in the same order for
## reference and data. Refactoring data to match.log_cm5## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 17079 1117
## 1 0 0
##
## Accuracy : 0.9386
## 95% CI : (0.935, 0.9421)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.508
##
## Kappa : 0
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.00000
## Specificity : 1.00000
## Pos Pred Value : NaN
## Neg Pred Value : 0.93861
## Prevalence : 0.06139
## Detection Rate : 0.00000
## Detection Prevalence : 0.00000
## Balanced Accuracy : 0.50000
##
## 'Positive' Class : 1
## Linear Regression with predictions
linear regression model 1
# First linear regression to estimate family income with test data set
linear_mod1 <- lm(FamilyIncome ~ FamilyType + FoodStamp + OwnRent + HouseCosts + Insurance + ElectricBill + NumRooms, data=acs_fit)
summary(linear_mod1)##
## Call:
## lm(formula = FamilyIncome ~ FamilyType + FoodStamp + OwnRent +
## HouseCosts + Insurance + ElectricBill + NumRooms, data = acs_fit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -372890 -39833 -9227 22628 1198390
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.550e+04 2.699e+03 -9.448 < 2e-16 ***
## FamilyTypeMale Head 8.939e+03 3.233e+03 2.765 0.0057 **
## FamilyTypeMarried 3.814e+04 1.866e+03 20.435 < 2e-16 ***
## FoodStampYes -2.614e+04 2.485e+03 -10.519 < 2e-16 ***
## OwnRentOutright 4.074e+04 7.468e+03 5.455 4.95e-08 ***
## OwnRentRented -1.391e+03 2.241e+03 -0.620 0.5350
## HouseCosts 2.738e+01 6.451e-01 42.439 < 2e-16 ***
## Insurance 1.839e+01 7.637e-01 24.078 < 2e-16 ***
## ElectricBill 5.154e+01 6.313e+00 8.163 3.48e-16 ***
## NumRooms 5.537e+03 2.793e+02 19.823 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 83680 on 18186 degrees of freedom
## Multiple R-squared: 0.3138, Adjusted R-squared: 0.3135
## F-statistic: 924.1 on 9 and 18186 DF, p-value: < 2.2e-16linear regression model 2
# Created another linear regression to estimate family income with test data set to be used for predicting high income
linear_mod2 <- lm(FamilyIncome ~ Insurance + HouseCosts + ElectricBill + NumWorkers + FamilyType + FoodStamp + OwnRent + NumBedrooms + NumChildren + NumRooms + NumPeople + NumVehicles + Language, data=acs_fit)
summary(linear_mod2)##
## Call:
## lm(formula = FamilyIncome ~ Insurance + HouseCosts + ElectricBill +
## NumWorkers + FamilyType + FoodStamp + OwnRent + NumBedrooms +
## NumChildren + NumRooms + NumPeople + NumVehicles + Language,
## data = acs_fit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -386370 -37621 -9512 20578 1182262
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.907e+04 4.482e+03 -10.947 < 2e-16 ***
## Insurance 1.891e+01 7.552e-01 25.047 < 2e-16 ***
## HouseCosts 2.791e+01 6.532e-01 42.723 < 2e-16 ***
## ElectricBill 4.849e+01 6.330e+00 7.659 1.96e-14 ***
## NumWorkers 1.865e+04 8.823e+02 21.136 < 2e-16 ***
## FamilyTypeMale Head 7.558e+03 3.179e+03 2.378 0.017433 *
## FamilyTypeMarried 3.036e+04 1.875e+03 16.191 < 2e-16 ***
## FoodStampYes -1.214e+04 2.548e+03 -4.766 1.89e-06 ***
## OwnRentOutright 5.753e+04 7.362e+03 7.814 5.83e-15 ***
## OwnRentRented 7.785e+03 2.241e+03 3.474 0.000513 ***
## NumBedrooms 2.337e+03 7.579e+02 3.083 0.002050 **
## NumChildren 3.963e+03 7.790e+02 5.087 3.67e-07 ***
## NumRooms 4.482e+03 3.381e+02 13.254 < 2e-16 ***
## NumPeople -7.638e+03 7.218e+02 -10.582 < 2e-16 ***
## NumVehicles 7.058e+03 7.393e+02 9.547 < 2e-16 ***
## LanguageEnglish 3.073e+03 3.400e+03 0.904 0.366076
## LanguageOther -1.447e+03 6.383e+03 -0.227 0.820722
## LanguageOther European -1.789e+03 3.850e+03 -0.465 0.642238
## LanguageSpanish -9.829e+03 3.931e+03 -2.500 0.012415 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 82010 on 18177 degrees of freedom
## Multiple R-squared: 0.3413, Adjusted R-squared: 0.3407
## F-statistic: 523.3 on 18 and 18177 DF, p-value: < 2.2e-16linear_mod2$fitted.values[1:25]## 2 3 4 5 7 9
## 15265.280 228892.405 37156.304 17581.839 -6974.918 53527.675
## 12 15 16 17 18 19
## -22107.414 33577.098 15333.216 91891.787 32025.055 59505.001
## 20 21 22 23 24 25
## 6686.889 -14647.771 6025.054 27790.468 70487.493 21273.056
## 26 27 28 29 30 31
## 60002.227 27223.323 9341.574 18643.608 97219.909 1705.970
## 32
## 8496.231acs_fit$linest_HighIncome <- ifelse(linear_mod2$fit > 250000,1,0)
linear_cm2 <- confusionMatrix(as.factor(acs_fit$linest_HighIncome), as.factor(acs_fit$HighIncome), positive = "1")
linear_cm2## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 16862 857
## 1 217 260
##
## Accuracy : 0.941
## 95% CI : (0.9375, 0.9444)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.0941
##
## Kappa : 0.3005
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.23277
## Specificity : 0.98729
## Pos Pred Value : 0.54507
## Neg Pred Value : 0.95163
## Prevalence : 0.06139
## Detection Rate : 0.01429
## Detection Prevalence : 0.02621
## Balanced Accuracy : 0.61003
##
## 'Positive' Class : 1
## Regression Model Comparison
Could not get it to work how I wanted - I have the big chunk of code if you want to see it!
DECISION TREES
Decision tree 1
tree1 <- rpart(HighIncome ~ FamilyType + HouseCosts + NumWorkers2 + OwnRent + Insurance + NumWorkers2 + YearBuilt + NumBedrooms, data=acs_fit, method="class")
rpart.plot(tree1)
tree1## n= 18196
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 18196 1117 0 (0.93861288 0.06138712)
## 2) HouseCosts< 3440 17218 723 0 (0.95800906 0.04199094) *
## 3) HouseCosts>=3440 978 394 0 (0.59713701 0.40286299)
## 6) HouseCosts< 4450 575 167 0 (0.70956522 0.29043478) *
## 7) HouseCosts>=4450 403 176 1 (0.43672457 0.56327543) *head(predict(tree1))## 0 1
## 2 0.9580091 0.04199094
## 3 0.9580091 0.04199094
## 4 0.9580091 0.04199094
## 5 0.9580091 0.04199094
## 7 0.9580091 0.04199094
## 9 0.9580091 0.04199094head(predict(tree1, type="class"))## 2 3 4 5 7 9
## 0 0 0 0 0 0
## Levels: 0 1tree1_cm <- confusionMatrix(predict(tree1, type="class"), acs_fit$HighIncome, positive = "1")
tree1_cm## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 16903 890
## 1 176 227
##
## Accuracy : 0.9414
## 95% CI : (0.9379, 0.9448)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.05864
##
## Kappa : 0.2751
## Mcnemar's Test P-Value : < 2e-16
##
## Sensitivity : 0.20322
## Specificity : 0.98969
## Pos Pred Value : 0.56328
## Neg Pred Value : 0.94998
## Prevalence : 0.06139
## Detection Rate : 0.01248
## Detection Prevalence : 0.02215
## Balanced Accuracy : 0.59646
##
## 'Positive' Class : 1
## Decision tree 2
tree2 <- rpart(HighIncome ~ FoodStamp + Insurance + FamilyType, data=acs_fit, method="class", control=rpart.control(minsplit=2, cp=0))
rpart.plot(tree2)
tree2## n= 18196
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 18196 1117 0 (0.938612882 0.061387118)
## 2) Insurance< 1950 16258 611 0 (0.962418502 0.037581498)
## 4) Insurance< 995 11256 239 0 (0.978766880 0.021233120)
## 8) FamilyType=Female Head,Male Head 2482 18 0 (0.992747784 0.007252216) *
## 9) FamilyType=Married 8774 221 0 (0.974811944 0.025188056)
## 18) Insurance< 795 7261 161 0 (0.977826746 0.022173254)
## 36) Insurance>=265 5074 82 0 (0.983839180 0.016160820) *
## 37) Insurance< 265 2187 79 0 (0.963877458 0.036122542)
## 74) FoodStamp=Yes 264 0 0 (1.000000000 0.000000000) *
## 75) FoodStamp=No 1923 79 0 (0.958918357 0.041081643)
## 150) Insurance< 245 1832 73 0 (0.960152838 0.039847162)
## 300) Insurance>=25 357 8 0 (0.977591036 0.022408964) *
## 301) Insurance< 25 1475 65 0 (0.955932203 0.044067797)
## 602) Insurance< 12 1472 63 0 (0.957201087 0.042798913) *
## 603) Insurance>=12 3 1 1 (0.333333333 0.666666667) *
## 151) Insurance>=245 91 6 0 (0.934065934 0.065934066) *
## 19) Insurance>=795 1513 60 0 (0.960343688 0.039656312)
## 38) Insurance>=955 101 1 0 (0.990099010 0.009900990) *
## 39) Insurance< 955 1412 59 0 (0.958215297 0.041784703)
## 78) Insurance< 845 695 23 0 (0.966906475 0.033093525) *
## 79) Insurance>=845 717 36 0 (0.949790795 0.050209205)
## 158) Insurance>=855 623 29 0 (0.953451043 0.046548957)
## 316) Insurance>=945 68 2 0 (0.970588235 0.029411765) *
## 317) Insurance< 945 555 27 0 (0.951351351 0.048648649)
## 634) Insurance< 935 538 24 0 (0.955390335 0.044609665) *
## 635) Insurance>=935 17 3 0 (0.823529412 0.176470588)
## 1270) FoodStamp=No 16 2 0 (0.875000000 0.125000000) *
## 1271) FoodStamp=Yes 1 0 1 (0.000000000 1.000000000) *
## 159) Insurance< 855 94 7 0 (0.925531915 0.074468085) *
## 5) Insurance>=995 5002 372 0 (0.925629748 0.074370252) *
## 3) Insurance>=1950 1938 506 0 (0.738906089 0.261093911)
## 6) Insurance< 3650 1516 323 0 (0.786939314 0.213060686) *
## 7) Insurance>=3650 422 183 0 (0.566350711 0.433649289)
## 14) FamilyType=Female Head,Male Head 35 6 0 (0.828571429 0.171428571)
## 28) Insurance< 4350 12 1 0 (0.916666667 0.083333333) *
## 29) Insurance>=4350 23 5 0 (0.782608696 0.217391304)
## 58) Insurance>=4650 22 4 0 (0.818181818 0.181818182) *
## 59) Insurance< 4650 1 0 1 (0.000000000 1.000000000) *
## 15) FamilyType=Married 387 177 0 (0.542635659 0.457364341)
## 30) Insurance< 4750 157 62 0 (0.605095541 0.394904459)
## 60) Insurance>=4450 34 8 0 (0.764705882 0.235294118)
## 120) Insurance< 4550 26 5 0 (0.807692308 0.192307692) *
## 121) Insurance>=4550 8 3 0 (0.625000000 0.375000000)
## 242) Insurance>=4650 3 0 0 (1.000000000 0.000000000) *
## 243) Insurance< 4650 5 2 1 (0.400000000 0.600000000) *
## 61) Insurance< 4450 123 54 0 (0.560975610 0.439024390)
## 122) Insurance>=3850 109 46 0 (0.577981651 0.422018349)
## 244) Insurance< 4250 97 39 0 (0.597938144 0.402061856) *
## 245) Insurance>=4250 12 5 1 (0.416666667 0.583333333) *
## 123) Insurance< 3850 14 6 1 (0.428571429 0.571428571) *
## 31) Insurance>=4750 230 115 0 (0.500000000 0.500000000)
## 62) Insurance>=5800 218 106 0 (0.513761468 0.486238532) *
## 63) Insurance< 5800 12 3 1 (0.250000000 0.750000000) *head(predict(tree2))## 0 1
## 2 0.9927478 0.007252216
## 3 0.8181818 0.181818182
## 4 0.9927478 0.007252216
## 5 0.9927478 0.007252216
## 7 0.9927478 0.007252216
## 9 0.9256297 0.074370252head(predict(tree2, type="class"))## 2 3 4 5 7 9
## 0 0 0 0 0 0
## Levels: 0 1tree2_cm <- confusionMatrix(predict(tree2, type="class"), acs_fit$HighIncome, positive = "1")
tree2_cm## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 17062 1086
## 1 17 31
##
## Accuracy : 0.9394
## 95% CI : (0.9358, 0.9428)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.3397
##
## Kappa : 0.0484
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.027753
## Specificity : 0.999005
## Pos Pred Value : 0.645833
## Neg Pred Value : 0.940159
## Prevalence : 0.061387
## Detection Rate : 0.001704
## Detection Prevalence : 0.002638
## Balanced Accuracy : 0.513379
##
## 'Positive' Class : 1
## Decision tree 3
tree3 <- rpart(HighIncome ~ Insurance + ElectricBill + HouseCosts, data=acs_fit, method="class", control=rpart.control(minsplit=2, cp=.005))
rpart.plot(tree3)
tree3## n= 18196
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 18196 1117 0 (0.93861288 0.06138712)
## 2) HouseCosts< 3440 17218 723 0 (0.95800906 0.04199094) *
## 3) HouseCosts>=3440 978 394 0 (0.59713701 0.40286299)
## 6) HouseCosts< 4450 575 167 0 (0.70956522 0.29043478) *
## 7) HouseCosts>=4450 403 176 1 (0.43672457 0.56327543)
## 14) ElectricBill< 430 326 156 1 (0.47852761 0.52147239)
## 28) Insurance< 865 20 3 0 (0.85000000 0.15000000) *
## 29) Insurance>=865 306 139 1 (0.45424837 0.54575163)
## 58) Insurance< 2350 135 64 0 (0.52592593 0.47407407) *
## 59) Insurance>=2350 171 68 1 (0.39766082 0.60233918) *
## 15) ElectricBill>=430 77 20 1 (0.25974026 0.74025974) *head(predict(tree3))## 0 1
## 2 0.9580091 0.04199094
## 3 0.9580091 0.04199094
## 4 0.9580091 0.04199094
## 5 0.9580091 0.04199094
## 7 0.9580091 0.04199094
## 9 0.9580091 0.04199094head(predict(tree3, type="class"))## 2 3 4 5 7 9
## 0 0 0 0 0 0
## Levels: 0 1tree3_cm <- confusionMatrix(predict(tree3, type="class"), acs_fit$HighIncome, positive = "1")
tree3_cm## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 16991 957
## 1 88 160
##
## Accuracy : 0.9426
## 95% CI : (0.9391, 0.9459)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : 0.013
##
## Kappa : 0.217
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.143241
## Specificity : 0.994847
## Pos Pred Value : 0.645161
## Neg Pred Value : 0.946679
## Prevalence : 0.061387
## Detection Rate : 0.008793
## Detection Prevalence : 0.013629
## Balanced Accuracy : 0.569044
##
## 'Positive' Class : 1
## Decision tree 4
tree4 <- rpart(HighIncome ~ Insurance + ElectricBill + HouseCosts + NumBedrooms + NumChildren + NumPeople + NumRooms + NumVehicles + NumWorkers + FoodStamp + OwnRent + ElectricBill + HouseCosts, data=acs_fit, method="class", control=rpart.control(minsplit=2, cp=0))
rpart.plot(tree4)## Warning: labs do not fit even at cex 0.15, there may be some overplotting
tree4## n= 18196
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 18196 1117 0 (0.938612882 0.061387118)
## 2) HouseCosts< 3440 17218 723 0 (0.958009060 0.041990940)
## 4) Insurance< 1950 15794 480 0 (0.969608712 0.030391288)
## 8) HouseCosts< 1905 12585 243 0 (0.980691299 0.019308701)
## 16) Insurance< 995 9916 124 0 (0.987494958 0.012505042)
## 32) OwnRent=Mortgage,Rented 9816 113 0 (0.988488183 0.011511817)
## 64) HouseCosts< 995 6416 41 0 (0.993609726 0.006390274)
## 128) NumRooms< 11.5 6319 36 0 (0.994302896 0.005697104)
## 256) NumVehicles< 5.5 6295 34 0 (0.994598888 0.005401112)
## 512) HouseCosts>=65 6254 32 0 (0.994883275 0.005116725)
## 1024) NumWorkers< 1.5 2620 6 0 (0.997709924 0.002290076)
## 2048) NumVehicles< 1.5 1161 0 0 (1.000000000 0.000000000) *
## 2049) NumVehicles>=1.5 1459 6 0 (0.995887594 0.004112406)
## 4098) ElectricBill< 245 1324 4 0 (0.996978852 0.003021148)
## 8196) HouseCosts< 645 856 1 0 (0.998831776 0.001168224)
## 16392) NumChildren< 1.5 705 0 0 (1.000000000 0.000000000) *
## 16393) NumChildren>=1.5 151 1 0 (0.993377483 0.006622517)
## 32786) NumBedrooms>=2.5 135 0 0 (1.000000000 0.000000000) *
## 32787) NumBedrooms< 2.5 16 1 0 (0.937500000 0.062500000)
## 65574) ElectricBill>=85 14 0 0 (1.000000000 0.000000000) *
## 65575) ElectricBill< 85 2 1 0 (0.500000000 0.500000000)
## 131150) Insurance>=220 1 0 0 (1.000000000 0.000000000) *
## 131151) Insurance< 220 1 0 1 (0.000000000 1.000000000) *
## 8197) HouseCosts>=645 468 3 0 (0.993589744 0.006410256)
## 16394) HouseCosts>=655 437 2 0 (0.995423341 0.004576659)
## 32788) NumRooms< 9.5 406 1 0 (0.997536946 0.002463054)
## 65576) ElectricBill< 155 313 0 0 (1.000000000 0.000000000) *
## 65577) ElectricBill>=155 93 1 0 (0.989247312 0.010752688)
## 131154) ElectricBill>=165 73 0 0 (1.000000000 0.000000000) *
## 131155) ElectricBill< 165 20 1 0 (0.950000000 0.050000000)
## 262310) Insurance>=425 14 0 0 (1.000000000 0.000000000) *
## 262311) Insurance< 425 6 1 0 (0.833333333 0.166666667)
## 524622) Insurance< 380 5 0 0 (1.000000000 0.000000000) *
## 524623) Insurance>=380 1 0 1 (0.000000000 1.000000000) *
## 32789) NumRooms>=9.5 31 1 0 (0.967741935 0.032258065)
## 65578) OwnRent=Mortgage 25 0 0 (1.000000000 0.000000000) *
## 65579) OwnRent=Rented 6 1 0 (0.833333333 0.166666667)
## 131158) NumChildren>=0.5 5 0 0 (1.000000000 0.000000000) *
## 131159) NumChildren< 0.5 1 0 1 (0.000000000 1.000000000) *
## 16395) HouseCosts< 655 31 1 0 (0.967741935 0.032258065)
## 32790) NumVehicles< 2.5 26 0 0 (1.000000000 0.000000000) *
## 32791) NumVehicles>=2.5 5 1 0 (0.800000000 0.200000000)
## 65582) NumRooms>=5.5 4 0 0 (1.000000000 0.000000000) *
## 65583) NumRooms< 5.5 1 0 1 (0.000000000 1.000000000) *
## 4099) ElectricBill>=245 135 2 0 (0.985185185 0.014814815)
## 8198) NumRooms>=4.5 123 1 0 (0.991869919 0.008130081)
## 16396) NumRooms< 8.5 102 0 0 (1.000000000 0.000000000) *
## 16397) NumRooms>=8.5 21 1 0 (0.952380952 0.047619048)
## 32794) ElectricBill>=255 17 0 0 (1.000000000 0.000000000) *
## 32795) ElectricBill< 255 4 1 0 (0.750000000 0.250000000)
## 65590) HouseCosts>=515 3 0 0 (1.000000000 0.000000000) *
## 65591) HouseCosts< 515 1 0 1 (0.000000000 1.000000000) *
## 8199) NumRooms< 4.5 12 1 0 (0.916666667 0.083333333)
## 16398) Insurance< 310 8 0 0 (1.000000000 0.000000000) *
## 16399) Insurance>=310 4 1 0 (0.750000000 0.250000000)
## 32798) Insurance>=370 3 0 0 (1.000000000 0.000000000) *
## 32799) Insurance< 370 1 0 1 (0.000000000 1.000000000) *
## 1025) NumWorkers>=1.5 3634 26 0 (0.992845349 0.007154651)
## 2050) NumChildren< 2.5 3364 21 0 (0.993757432 0.006242568)
## 4100) NumChildren>=1.5 628 1 0 (0.998407643 0.001592357)
## 8200) ElectricBill< 245 565 0 0 (1.000000000 0.000000000) *
## 8201) ElectricBill>=245 63 1 0 (0.984126984 0.015873016)
## 16402) ElectricBill>=255 46 0 0 (1.000000000 0.000000000) *
## 16403) ElectricBill< 255 17 1 0 (0.941176471 0.058823529)
## 32806) Insurance>=275 14 0 0 (1.000000000 0.000000000) *
## 32807) Insurance< 275 3 1 0 (0.666666667 0.333333333)
## 65614) Insurance< 125 2 0 0 (1.000000000 0.000000000) *
## 65615) Insurance>=125 1 0 1 (0.000000000 1.000000000) *
## 4101) NumChildren< 1.5 2736 20 0 (0.992690058 0.007309942)
## 8202) NumRooms< 5.5 682 2 0 (0.997067449 0.002932551)
## 16404) NumBedrooms< 3.5 668 1 0 (0.998502994 0.001497006)
## 32808) ElectricBill>=35 641 0 0 (1.000000000 0.000000000) *
## 32809) ElectricBill< 35 27 1 0 (0.962962963 0.037037037)
## 65618) HouseCosts< 870 24 0 0 (1.000000000 0.000000000) *
## 65619) HouseCosts>=870 3 1 0 (0.666666667 0.333333333)
## 131238) NumRooms>=4 2 0 0 (1.000000000 0.000000000) *
## 131239) NumRooms< 4 1 0 1 (0.000000000 1.000000000) *
## 16405) NumBedrooms>=3.5 14 1 0 (0.928571429 0.071428571)
## 32810) ElectricBill< 235 12 0 0 (1.000000000 0.000000000) *
## 32811) ElectricBill>=235 2 1 0 (0.500000000 0.500000000)
## 65622) Insurance>=180 1 0 0 (1.000000000 0.000000000) *
## 65623) Insurance< 180 1 0 1 (0.000000000 1.000000000) *
## 8203) NumRooms>=5.5 2054 18 0 (0.991236611 0.008763389)
## 16406) NumVehicles>=1.5 1868 14 0 (0.992505353 0.007494647)
## 32812) Insurance>=785 244 0 0 (1.000000000 0.000000000) *
## 32813) Insurance< 785 1624 14 0 (0.991379310 0.008620690)
## 65626) Insurance< 775 1612 13 0 (0.991935484 0.008064516)
## 131252) NumVehicles< 2.5 893 5 0 (0.994400896 0.005599104)
## 262504) Insurance< 745 871 4 0 (0.995407577 0.004592423)
## 525008) HouseCosts>=405 693 2 0 (0.997113997 0.002886003)
## 1050016) NumRooms>=6.5 437 0 0 (1.000000000 0.000000000) *
## 1050017) NumRooms< 6.5 256 2 0 (0.992187500 0.007812500)
## 2100034) NumBedrooms< 3.5 236 1 0 (0.995762712 0.004237288)
## 4200068) NumBedrooms>=2.5 191 0 0 (1.000000000 0.000000000) *
## 4200069) NumBedrooms< 2.5 45 1 0 (0.977777778 0.022222222)
## 8400138) HouseCosts< 785 27 0 0 (1.000000000 0.000000000) *
## 8400139) HouseCosts>=785 18 1 0 (0.944444444 0.055555556)
## 16800278) HouseCosts>=795 16 0 0 (1.000000000 0.000000000) *
## 16800279) HouseCosts< 795 2 1 0 (0.500000000 0.500000000)
## 33600558) ElectricBill>=135 1 0 0 (1.000000000 0.000000000) *
## 33600559) ElectricBill< 135 1 0 1 (0.000000000 1.000000000) *
## 2100035) NumBedrooms>=3.5 20 1 0 (0.950000000 0.050000000)
## 4200070) ElectricBill< 195 16 0 0 (1.000000000 0.000000000) *
## 4200071) ElectricBill>=195 4 1 0 (0.750000000 0.250000000)
## 8400142) NumPeople>=2.5 3 0 0 (1.000000000 0.000000000) *
## 8400143) NumPeople< 2.5 1 0 1 (0.000000000 1.000000000) *
## 525009) HouseCosts< 405 178 2 0 (0.988764045 0.011235955)
## 1050018) Insurance< 625 166 1 0 (0.993975904 0.006024096)
## 2100036) HouseCosts>=275 97 0 0 (1.000000000 0.000000000) *
## 2100037) HouseCosts< 275 69 1 0 (0.985507246 0.014492754)
## 4200074) HouseCosts< 265 65 0 0 (1.000000000 0.000000000) *
## 4200075) HouseCosts>=265 4 1 0 (0.750000000 0.250000000)
## 8400150) Insurance< 425 3 0 0 (1.000000000 0.000000000) *
## 8400151) Insurance>=425 1 0 1 (0.000000000 1.000000000) *
## 1050019) Insurance>=625 12 1 0 (0.916666667 0.083333333)
## 2100038) Insurance>=665 11 0 0 (1.000000000 0.000000000) *
## 2100039) Insurance< 665 1 0 1 (0.000000000 1.000000000) *
## 262505) Insurance>=745 22 1 0 (0.954545455 0.045454545)
## 525010) HouseCosts< 740 15 0 0 (1.000000000 0.000000000) *
## 525011) HouseCosts>=740 7 1 0 (0.857142857 0.142857143)
## 1050022) HouseCosts>=765 6 0 0 (1.000000000 0.000000000) *
## 1050023) HouseCosts< 765 1 0 1 (0.000000000 1.000000000) *
## 131253) NumVehicles>=2.5 719 8 0 (0.988873435 0.011126565)
## 262506) HouseCosts< 925 670 6 0 (0.991044776 0.008955224)
## 525012) Insurance>=305 515 2 0 (0.996116505 0.003883495)
## 1050024) NumBedrooms< 4.5 491 1 0 (0.997963340 0.002036660)
## 2100048) HouseCosts< 835 419 0 0 (1.000000000 0.000000000) *
## 2100049) HouseCosts>=835 72 1 0 (0.986111111 0.013888889)
## 4200098) HouseCosts>=845 64 0 0 (1.000000000 0.000000000) *
## 4200099) HouseCosts< 845 8 1 0 (0.875000000 0.125000000)
## 8400198) ElectricBill< 165 6 0 0 (1.000000000 0.000000000) *
## 8400199) ElectricBill>=165 2 1 0 (0.500000000 0.500000000)
## 16800398) Insurance< 505 1 0 0 (1.000000000 0.000000000) *
## 16800399) Insurance>=505 1 0 1 (0.000000000 1.000000000) *
## 1050025) NumBedrooms>=4.5 24 1 0 (0.958333333 0.041666667)
## 2100050) HouseCosts>=380 20 0 0 (1.000000000 0.000000000) *
## 2100051) HouseCosts< 380 4 1 0 (0.750000000 0.250000000)
## 4200102) ElectricBill< 135 3 0 0 (1.000000000 0.000000000) *
## 4200103) ElectricBill>=135 1 0 1 (0.000000000 1.000000000) *
## 525013) Insurance< 305 155 4 0 (0.974193548 0.025806452)
## 1050026) NumBedrooms>=3.5 64 0 0 (1.000000000 0.000000000) *
## 1050027) NumBedrooms< 3.5 91 4 0 (0.956043956 0.043956044)
## 2100054) Insurance< 290 71 2 0 (0.971830986 0.028169014)
## 4200108) NumPeople< 4.5 61 1 0 (0.983606557 0.016393443)
## 8400216) NumBedrooms>=2.5 51 0 0 (1.000000000 0.000000000) *
## 8400217) NumBedrooms< 2.5 10 1 0 (0.900000000 0.100000000)
## 16800434) ElectricBill< 135 8 0 0 (1.000000000 0.000000000) *
## 16800435) ElectricBill>=135 2 1 0 (0.500000000 0.500000000)
## 33600870) Insurance>=2 1 0 0 (1.000000000 0.000000000) *
## 33600871) Insurance< 2 1 0 1 (0.000000000 1.000000000) *
## 4200109) NumPeople>=4.5 10 1 0 (0.900000000 0.100000000)
## 8400218) ElectricBill>=125 7 0 0 (1.000000000 0.000000000) *
## 8400219) ElectricBill< 125 3 1 0 (0.666666667 0.333333333)
## 16800438) ElectricBill< 115 2 0 0 (1.000000000 0.000000000) *
## 16800439) ElectricBill>=115 1 0 1 (0.000000000 1.000000000) *
## 2100055) Insurance>=290 20 2 0 (0.900000000 0.100000000)
## 4200110) ElectricBill>=105 13 0 0 (1.000000000 0.000000000) *
## 4200111) ElectricBill< 105 7 2 0 (0.714285714 0.285714286)
## 8400222) NumRooms>=6.5 3 0 0 (1.000000000 0.000000000) *
## 8400223) NumRooms< 6.5 4 2 0 (0.500000000 0.500000000)
## 16800446) ElectricBill< 90 3 1 0 (0.666666667 0.333333333)
## 33600892) ElectricBill>=70 1 0 0 (1.000000000 0.000000000) *
## 33600893) ElectricBill< 70 2 1 0 (0.500000000 0.500000000)
## 67201786) HouseCosts>=730 1 0 0 (1.000000000 0.000000000) *
## 67201787) HouseCosts< 730 1 0 1 (0.000000000 1.000000000) *
## 16800447) ElectricBill>=90 1 0 1 (0.000000000 1.000000000) *
## 262507) HouseCosts>=925 49 2 0 (0.959183673 0.040816327)
## 525014) Insurance< 690 45 1 0 (0.977777778 0.022222222)
## 1050028) ElectricBill< 240 39 0 0 (1.000000000 0.000000000) *
## 1050029) ElectricBill>=240 6 1 0 (0.833333333 0.166666667)
## 2100058) Insurance< 490 4 0 0 (1.000000000 0.000000000) *
## 2100059) Insurance>=490 2 1 0 (0.500000000 0.500000000)
## 4200118) Insurance>=580 1 0 0 (1.000000000 0.000000000) *
## 4200119) Insurance< 580 1 0 1 (0.000000000 1.000000000) *
## 525015) Insurance>=690 4 1 0 (0.750000000 0.250000000)
## 1050030) HouseCosts>=960 2 0 0 (1.000000000 0.000000000) *
## 1050031) HouseCosts< 960 2 1 0 (0.500000000 0.500000000)
## 2100062) ElectricBill>=225 1 0 0 (1.000000000 0.000000000) *
## 2100063) ElectricBill< 225 1 0 1 (0.000000000 1.000000000) *
## 65627) Insurance>=775 12 1 0 (0.916666667 0.083333333)
## 131254) HouseCosts>=235 10 0 0 (1.000000000 0.000000000) *
## 131255) HouseCosts< 235 2 1 0 (0.500000000 0.500000000)
## 262510) ElectricBill>=200 1 0 0 (1.000000000 0.000000000) *
## 262511) ElectricBill< 200 1 0 1 (0.000000000 1.000000000) *
## 16407) NumVehicles< 1.5 186 4 0 (0.978494624 0.021505376)
## 32814) Insurance< 495 115 0 0 (1.000000000 0.000000000) *
## 32815) Insurance>=495 71 4 0 (0.943661972 0.056338028)
## 65630) Insurance>=510 63 2 0 (0.968253968 0.031746032)
## 131260) ElectricBill>=65 49 0 0 (1.000000000 0.000000000) *
## 131261) ElectricBill< 65 14 2 0 (0.857142857 0.142857143)
## 262522) NumRooms< 8.5 13 1 0 (0.923076923 0.076923077)
## 525044) HouseCosts< 845 10 0 0 (1.000000000 0.000000000) *
## 525045) HouseCosts>=845 3 1 0 (0.666666667 0.333333333)
## 1050090) HouseCosts>=895 2 0 0 (1.000000000 0.000000000) *
## 1050091) HouseCosts< 895 1 0 1 (0.000000000 1.000000000) *
## 262523) NumRooms>=8.5 1 0 1 (0.000000000 1.000000000) *
## 65631) Insurance< 510 8 2 0 (0.750000000 0.250000000)
## 131262) ElectricBill>=75 7 1 0 (0.857142857 0.142857143)
## 262524) ElectricBill< 185 6 0 0 (1.000000000 0.000000000) *
## 262525) ElectricBill>=185 1 0 1 (0.000000000 1.000000000) *
## 131263) ElectricBill< 75 1 0 1 (0.000000000 1.000000000) *
## 2051) NumChildren>=2.5 270 5 0 (0.981481481 0.018518519)
## 4102) NumRooms< 10.5 258 3 0 (0.988372093 0.011627907)
## 8204) NumPeople>=4.5 253 2 0 (0.992094862 0.007905138)
## 16408) ElectricBill< 145 142 0 0 (1.000000000 0.000000000) *
## 16409) ElectricBill>=145 111 2 0 (0.981981982 0.018018018)
## 32818) NumBedrooms>=3.5 55 0 0 (1.000000000 0.000000000) *
## 32819) NumBedrooms< 3.5 56 2 0 (0.964285714 0.035714286)
## 65638) NumPeople< 6.5 52 1 0 (0.980769231 0.019230769)
## 131276) FoodStamp=No 45 0 0 (1.000000000 0.000000000) *
## 131277) FoodStamp=Yes 7 1 0 (0.857142857 0.142857143)
## 262554) HouseCosts< 860 6 0 0 (1.000000000 0.000000000) *
## 262555) HouseCosts>=860 1 0 1 (0.000000000 1.000000000) *
## 65639) NumPeople>=6.5 4 1 0 (0.750000000 0.250000000)
## 131278) ElectricBill>=155 3 0 0 (1.000000000 0.000000000) *
## 131279) ElectricBill< 155 1 0 1 (0.000000000 1.000000000) *
## 8205) NumPeople< 4.5 5 1 0 (0.800000000 0.200000000)
## 16410) HouseCosts< 825 4 0 0 (1.000000000 0.000000000) *
## 16411) HouseCosts>=825 1 0 1 (0.000000000 1.000000000) *
## 4103) NumRooms>=10.5 12 2 0 (0.833333333 0.166666667)
## 8206) NumVehicles>=2.5 8 0 0 (1.000000000 0.000000000) *
## 8207) NumVehicles< 2.5 4 2 0 (0.500000000 0.500000000)
## 16414) NumBedrooms< 4.5 2 0 0 (1.000000000 0.000000000) *
## 16415) NumBedrooms>=4.5 2 0 1 (0.000000000 1.000000000) *
## 513) HouseCosts< 65 41 2 0 (0.951219512 0.048780488)
## 1026) ElectricBill>=45 37 1 0 (0.972972973 0.027027027)
## 2052) NumVehicles< 3.5 32 0 0 (1.000000000 0.000000000) *
## 2053) NumVehicles>=3.5 5 1 0 (0.800000000 0.200000000)
## 4106) NumWorkers>=1.5 4 0 0 (1.000000000 0.000000000) *
## 4107) NumWorkers< 1.5 1 0 1 (0.000000000 1.000000000) *
## 1027) ElectricBill< 45 4 1 0 (0.750000000 0.250000000)
## 2054) NumBedrooms>=2.5 3 0 0 (1.000000000 0.000000000) *
## 2055) NumBedrooms< 2.5 1 0 1 (0.000000000 1.000000000) *
## 257) NumVehicles>=5.5 24 2 0 (0.916666667 0.083333333)
## 514) HouseCosts< 730 14 0 0 (1.000000000 0.000000000) *
## 515) HouseCosts>=730 10 2 0 (0.800000000 0.200000000)
## 1030) HouseCosts>=785 8 0 0 (1.000000000 0.000000000) *
## 1031) HouseCosts< 785 2 0 1 (0.000000000 1.000000000) *
## 129) NumRooms>=11.5 97 5 0 (0.948453608 0.051546392)
## 258) ElectricBill< 320 85 3 0 (0.964705882 0.035294118)
## 516) ElectricBill>=145 43 0 0 (1.000000000 0.000000000) *
## 517) ElectricBill< 145 42 3 0 (0.928571429 0.071428571)
## 1034) ElectricBill< 135 38 1 0 (0.973684211 0.026315789)
## 2068) HouseCosts< 855 32 0 0 (1.000000000 0.000000000) *
## 2069) HouseCosts>=855 6 1 0 (0.833333333 0.166666667)
## 4138) Insurance>=525 5 0 0 (1.000000000 0.000000000) *
## 4139) Insurance< 525 1 0 1 (0.000000000 1.000000000) *
## 1035) ElectricBill>=135 4 2 0 (0.500000000 0.500000000)
## 2070) HouseCosts>=555 2 0 0 (1.000000000 0.000000000) *
## 2071) HouseCosts< 555 2 0 1 (0.000000000 1.000000000) *
## 259) ElectricBill>=320 12 2 0 (0.833333333 0.166666667)
## 518) ElectricBill>=335 11 1 0 (0.909090909 0.090909091)
## 1036) NumChildren< 3.5 10 0 0 (1.000000000 0.000000000) *
## 1037) NumChildren>=3.5 1 0 1 (0.000000000 1.000000000) *
## 519) ElectricBill< 335 1 0 1 (0.000000000 1.000000000) *
## 65) HouseCosts>=995 3400 72 0 (0.978823529 0.021176471)
## 130) NumRooms< 7.5 2234 32 0 (0.985675918 0.014324082)
## 260) NumPeople< 11.5 2233 31 0 (0.986117331 0.013882669)
## 520) Insurance< 845 2016 23 0 (0.988591270 0.011408730)
## 1040) NumPeople>=2.5 1325 9 0 (0.993207547 0.006792453)
## 2080) NumVehicles< 4.5 1312 8 0 (0.993902439 0.006097561)
## 4160) ElectricBill< 335 1229 6 0 (0.995117982 0.004882018)
## 8320) NumChildren< 3.5 1190 5 0 (0.995798319 0.004201681)
## 16640) ElectricBill>=65 1050 3 0 (0.997142857 0.002857143)
## 33280) HouseCosts< 1565 777 1 0 (0.998712999 0.001287001)
## 66560) Insurance< 695 625 0 0 (1.000000000 0.000000000) *
## 66561) Insurance>=695 152 1 0 (0.993421053 0.006578947)
## 133122) Insurance>=705 106 0 0 (1.000000000 0.000000000) *
## 133123) Insurance< 705 46 1 0 (0.978260870 0.021739130)
## 266246) NumRooms>=5.5 35 0 0 (1.000000000 0.000000000) *
## 266247) NumRooms< 5.5 11 1 0 (0.909090909 0.090909091)
## 532494) ElectricBill>=125 7 0 0 (1.000000000 0.000000000) *
## 532495) ElectricBill< 125 4 1 0 (0.750000000 0.250000000)
## 1064990) ElectricBill< 110 3 0 0 (1.000000000 0.000000000) *
## 1064991) ElectricBill>=110 1 0 1 (0.000000000 1.000000000) *
## 33281) HouseCosts>=1565 273 2 0 (0.992673993 0.007326007)
## 66562) NumRooms>=4.5 246 1 0 (0.995934959 0.004065041)
## 133124) NumVehicles>=1.5 187 0 0 (1.000000000 0.000000000) *
## 133125) NumVehicles< 1.5 59 1 0 (0.983050847 0.016949153)
## 266250) HouseCosts>=1650 36 0 0 (1.000000000 0.000000000) *
## 266251) HouseCosts< 1650 23 1 0 (0.956521739 0.043478261)
## 532502) ElectricBill< 190 13 0 0 (1.000000000 0.000000000) *
## 532503) ElectricBill>=190 10 1 0 (0.900000000 0.100000000)
## 1065006) NumPeople>=3.5 9 0 0 (1.000000000 0.000000000) *
## 1065007) NumPeople< 3.5 1 0 1 (0.000000000 1.000000000) *
## 66563) NumRooms< 4.5 27 1 0 (0.962962963 0.037037037)
## 133126) ElectricBill< 160 18 0 0 (1.000000000 0.000000000) *
## 133127) ElectricBill>=160 9 1 0 (0.888888889 0.111111111)
## 266254) ElectricBill>=185 8 0 0 (1.000000000 0.000000000) *
## 266255) ElectricBill< 185 1 0 1 (0.000000000 1.000000000) *
## 16641) ElectricBill< 65 140 2 0 (0.985714286 0.014285714)
## 33282) NumVehicles< 2.5 124 0 0 (1.000000000 0.000000000) *
## 33283) NumVehicles>=2.5 16 2 0 (0.875000000 0.125000000)
## 66566) HouseCosts< 1550 15 1 0 (0.933333333 0.066666667)
## 133132) NumBedrooms>=2.5 12 0 0 (1.000000000 0.000000000) *
## 133133) NumBedrooms< 2.5 3 1 0 (0.666666667 0.333333333)
## 266266) Insurance< 175 2 0 0 (1.000000000 0.000000000) *
## 266267) Insurance>=175 1 0 1 (0.000000000 1.000000000) *
## 66567) HouseCosts>=1550 1 0 1 (0.000000000 1.000000000) *
## 8321) NumChildren>=3.5 39 1 0 (0.974358974 0.025641026)
## 16642) NumVehicles< 2.5 36 0 0 (1.000000000 0.000000000) *
## 16643) NumVehicles>=2.5 3 1 0 (0.666666667 0.333333333)
## 33286) NumBedrooms>=3.5 2 0 0 (1.000000000 0.000000000) *
## 33287) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 4161) ElectricBill>=335 83 2 0 (0.975903614 0.024096386)
## 8322) HouseCosts>=1050 76 1 0 (0.986842105 0.013157895)
## 16644) ElectricBill>=345 69 0 0 (1.000000000 0.000000000) *
## 16645) ElectricBill< 345 7 1 0 (0.857142857 0.142857143)
## 33290) Insurance< 740 6 0 0 (1.000000000 0.000000000) *
## 33291) Insurance>=740 1 0 1 (0.000000000 1.000000000) *
## 8323) HouseCosts< 1050 7 1 0 (0.857142857 0.142857143)
## 16646) NumChildren>=0.5 6 0 0 (1.000000000 0.000000000) *
## 16647) NumChildren< 0.5 1 0 1 (0.000000000 1.000000000) *
## 2081) NumVehicles>=4.5 13 1 0 (0.923076923 0.076923077)
## 4162) Insurance< 795 12 0 0 (1.000000000 0.000000000) *
## 4163) Insurance>=795 1 0 1 (0.000000000 1.000000000) *
## 1041) NumPeople< 2.5 691 14 0 (0.979739508 0.020260492)
## 2082) ElectricBill>=1.5 674 12 0 (0.982195846 0.017804154)
## 4164) HouseCosts< 1665 594 7 0 (0.988215488 0.011784512)
## 8328) NumVehicles< 1.5 164 0 0 (1.000000000 0.000000000) *
## 8329) NumVehicles>=1.5 430 7 0 (0.983720930 0.016279070)
## 16658) NumBedrooms>=1.5 417 6 0 (0.985611511 0.014388489)
## 33316) Insurance< 245 90 0 0 (1.000000000 0.000000000) *
## 33317) Insurance>=245 327 6 0 (0.981651376 0.018348624)
## 66634) Insurance>=280 322 4 0 (0.987577640 0.012422360)
## 133268) Insurance< 705 258 2 0 (0.992248062 0.007751938)
## 266536) Insurance>=505 131 0 0 (1.000000000 0.000000000) *
## 266537) Insurance< 505 127 2 0 (0.984251969 0.015748031)
## 533074) Insurance< 475 73 0 0 (1.000000000 0.000000000) *
## 533075) Insurance>=475 54 2 0 (0.962962963 0.037037037)
## 1066150) Insurance>=485 48 1 0 (0.979166667 0.020833333)
## 2132300) HouseCosts>=1050 43 0 0 (1.000000000 0.000000000) *
## 2132301) HouseCosts< 1050 5 1 0 (0.800000000 0.200000000)
## 4264602) ElectricBill>=90 3 0 0 (1.000000000 0.000000000) *
## 4264603) ElectricBill< 90 2 1 0 (0.500000000 0.500000000)
## 8529206) ElectricBill< 60 1 0 0 (1.000000000 0.000000000) *
## 8529207) ElectricBill>=60 1 0 1 (0.000000000 1.000000000) *
## 1066151) Insurance< 485 6 1 0 (0.833333333 0.166666667)
## 2132302) ElectricBill>=110 5 0 0 (1.000000000 0.000000000) *
## 2132303) ElectricBill< 110 1 0 1 (0.000000000 1.000000000) *
## 133269) Insurance>=705 64 2 0 (0.968750000 0.031250000)
## 266538) Insurance>=715 61 1 0 (0.983606557 0.016393443)
## 533076) ElectricBill>=105 40 0 0 (1.000000000 0.000000000) *
## 533077) ElectricBill< 105 21 1 0 (0.952380952 0.047619048)
## 1066154) ElectricBill< 95 12 0 0 (1.000000000 0.000000000) *
## 1066155) ElectricBill>=95 9 1 0 (0.888888889 0.111111111)
## 2132310) Insurance< 785 5 0 0 (1.000000000 0.000000000) *
## 2132311) Insurance>=785 4 1 0 (0.750000000 0.250000000)
## 4264622) Insurance>=810 1 0 0 (1.000000000 0.000000000) *
## 4264623) Insurance< 810 3 1 0 (0.666666667 0.333333333)
## 8529246) HouseCosts< 1250 1 0 0 (1.000000000 0.000000000) *
## 8529247) HouseCosts>=1250 2 1 0 (0.500000000 0.500000000)
## 17058494) HouseCosts>=1400 1 0 0 (1.000000000 0.000000000) *
## 17058495) HouseCosts< 1400 1 0 1 (0.000000000 1.000000000) *
## 266539) Insurance< 715 3 1 0 (0.666666667 0.333333333)
## 533078) NumRooms< 6.5 2 0 0 (1.000000000 0.000000000) *
## 533079) NumRooms>=6.5 1 0 1 (0.000000000 1.000000000) *
## 66635) Insurance< 280 5 2 0 (0.600000000 0.400000000)
## 133270) ElectricBill< 130 2 0 0 (1.000000000 0.000000000) *
## 133271) ElectricBill>=130 3 1 1 (0.333333333 0.666666667)
## 266542) Insurance< 255 2 1 0 (0.500000000 0.500000000)
## 533084) ElectricBill< 195 1 0 0 (1.000000000 0.000000000) *
## 533085) ElectricBill>=195 1 0 1 (0.000000000 1.000000000) *
## 266543) Insurance>=255 1 0 1 (0.000000000 1.000000000) *
## 16659) NumBedrooms< 1.5 13 1 0 (0.923076923 0.076923077)
## 33318) OwnRent=Rented 8 0 0 (1.000000000 0.000000000) *
## 33319) OwnRent=Mortgage 5 1 0 (0.800000000 0.200000000)
## 66638) Insurance>=225 3 0 0 (1.000000000 0.000000000) *
## 66639) Insurance< 225 2 1 0 (0.500000000 0.500000000)
## 133278) ElectricBill>=185 1 0 0 (1.000000000 0.000000000) *
## 133279) ElectricBill< 185 1 0 1 (0.000000000 1.000000000) *
## 4165) HouseCosts>=1665 80 5 0 (0.937500000 0.062500000)
## 8330) HouseCosts>=1685 79 4 0 (0.949367089 0.050632911)
## 16660) NumVehicles< 1.5 23 0 0 (1.000000000 0.000000000) *
## 16661) NumVehicles>=1.5 56 4 0 (0.928571429 0.071428571)
## 33322) NumChildren< 0.5 55 3 0 (0.945454545 0.054545455)
## 66644) ElectricBill>=95 42 1 0 (0.976190476 0.023809524)
## 133288) NumRooms>=4.5 36 0 0 (1.000000000 0.000000000) *
## 133289) NumRooms< 4.5 6 1 0 (0.833333333 0.166666667)
## 266578) HouseCosts>=1750 5 0 0 (1.000000000 0.000000000) *
## 266579) HouseCosts< 1750 1 0 1 (0.000000000 1.000000000) *
## 66645) ElectricBill< 95 13 2 0 (0.846153846 0.153846154)
## 133290) ElectricBill< 75 8 0 0 (1.000000000 0.000000000) *
## 133291) ElectricBill>=75 5 2 0 (0.600000000 0.400000000)
## 266582) HouseCosts>=1850 2 0 0 (1.000000000 0.000000000) *
## 266583) HouseCosts< 1850 3 1 1 (0.333333333 0.666666667)
## 533166) Insurance>=750 1 0 0 (1.000000000 0.000000000) *
## 533167) Insurance< 750 2 0 1 (0.000000000 1.000000000) *
## 33323) NumChildren>=0.5 1 0 1 (0.000000000 1.000000000) *
## 8331) HouseCosts< 1685 1 0 1 (0.000000000 1.000000000) *
## 2083) ElectricBill< 1.5 17 2 0 (0.882352941 0.117647059)
## 4166) NumWorkers>=0.5 16 1 0 (0.937500000 0.062500000)
## 8332) NumBedrooms< 2.5 10 0 0 (1.000000000 0.000000000) *
## 8333) NumBedrooms>=2.5 6 1 0 (0.833333333 0.166666667)
## 16666) HouseCosts< 1300 3 0 0 (1.000000000 0.000000000) *
## 16667) HouseCosts>=1300 3 1 0 (0.666666667 0.333333333)
## 33334) HouseCosts>=1500 2 0 0 (1.000000000 0.000000000) *
## 33335) HouseCosts< 1500 1 0 1 (0.000000000 1.000000000) *
## 4167) NumWorkers< 0.5 1 0 1 (0.000000000 1.000000000) *
## 521) Insurance>=845 217 8 0 (0.963133641 0.036866359)
## 1042) Insurance>=875 174 2 0 (0.988505747 0.011494253)
## 2084) NumVehicles< 3.5 162 0 0 (1.000000000 0.000000000) *
## 2085) NumVehicles>=3.5 12 2 0 (0.833333333 0.166666667)
## 4170) ElectricBill< 225 11 1 0 (0.909090909 0.090909091)
## 8340) NumBedrooms< 3.5 9 0 0 (1.000000000 0.000000000) *
## 8341) NumBedrooms>=3.5 2 1 0 (0.500000000 0.500000000)
## 16682) Insurance< 920 1 0 0 (1.000000000 0.000000000) *
## 16683) Insurance>=920 1 0 1 (0.000000000 1.000000000) *
## 4171) ElectricBill>=225 1 0 1 (0.000000000 1.000000000) *
## 1043) Insurance< 875 43 6 0 (0.860465116 0.139534884)
## 2086) HouseCosts< 1750 39 4 0 (0.897435897 0.102564103)
## 4172) Insurance< 865 33 2 0 (0.939393939 0.060606061)
## 8344) NumBedrooms< 3.5 31 1 0 (0.967741935 0.032258065)
## 16688) ElectricBill< 205 22 0 0 (1.000000000 0.000000000) *
## 16689) ElectricBill>=205 9 1 0 (0.888888889 0.111111111)
## 33378) ElectricBill>=215 6 0 0 (1.000000000 0.000000000) *
## 33379) ElectricBill< 215 3 1 0 (0.666666667 0.333333333)
## 66758) NumBedrooms< 2.5 2 0 0 (1.000000000 0.000000000) *
## 66759) NumBedrooms>=2.5 1 0 1 (0.000000000 1.000000000) *
## 8345) NumBedrooms>=3.5 2 1 0 (0.500000000 0.500000000)
## 16690) ElectricBill>=175 1 0 0 (1.000000000 0.000000000) *
## 16691) ElectricBill< 175 1 0 1 (0.000000000 1.000000000) *
## 4173) Insurance>=865 6 2 0 (0.666666667 0.333333333)
## 8346) NumChildren>=0.5 4 0 0 (1.000000000 0.000000000) *
## 8347) NumChildren< 0.5 2 0 1 (0.000000000 1.000000000) *
## 2087) HouseCosts>=1750 4 2 0 (0.500000000 0.500000000)
## 4174) Insurance< 855 3 1 0 (0.666666667 0.333333333)
## 8348) ElectricBill>=125 1 0 0 (1.000000000 0.000000000) *
## 8349) ElectricBill< 125 2 1 0 (0.500000000 0.500000000)
## 16698) NumChildren>=0.5 1 0 0 (1.000000000 0.000000000) *
## 16699) NumChildren< 0.5 1 0 1 (0.000000000 1.000000000) *
## 4175) Insurance>=855 1 0 1 (0.000000000 1.000000000) *
## 261) NumPeople>=11.5 1 0 1 (0.000000000 1.000000000) *
## 131) NumRooms>=7.5 1166 40 0 (0.965694683 0.034305317)
## 262) ElectricBill< 395 1124 34 0 (0.969750890 0.030249110)
## 524) ElectricBill< 185 761 16 0 (0.978975033 0.021024967)
## 1048) NumBedrooms< 4.5 658 10 0 (0.984802432 0.015197568)
## 2096) HouseCosts< 1850 628 8 0 (0.987261146 0.012738854)
## 4192) Insurance< 495 183 0 0 (1.000000000 0.000000000) *
## 4193) Insurance>=495 445 8 0 (0.982022472 0.017977528)
## 8386) NumVehicles< 3.5 401 6 0 (0.985037406 0.014962594)
## 16772) NumRooms< 10.5 359 4 0 (0.988857939 0.011142061)
## 33544) Insurance< 920 342 3 0 (0.991228070 0.008771930)
## 67088) ElectricBill>=55 316 2 0 (0.993670886 0.006329114)
## 134176) NumPeople>=2.5 211 0 0 (1.000000000 0.000000000) *
## 134177) NumPeople< 2.5 105 2 0 (0.980952381 0.019047619)
## 268354) Insurance>=515 90 1 0 (0.988888889 0.011111111)
## 536708) HouseCosts< 1650 78 0 0 (1.000000000 0.000000000) *
## 536709) HouseCosts>=1650 12 1 0 (0.916666667 0.083333333)
## 1073418) NumVehicles>=1.5 9 0 0 (1.000000000 0.000000000) *
## 1073419) NumVehicles< 1.5 3 1 0 (0.666666667 0.333333333)
## 2146838) Insurance< 750 2 0 0 (1.000000000 0.000000000) *
## 2146839) Insurance>=750 1 0 1 (0.000000000 1.000000000) *
## 268355) Insurance< 515 15 1 0 (0.933333333 0.066666667)
## 536710) ElectricBill< 150 11 0 0 (1.000000000 0.000000000) *
## 536711) ElectricBill>=150 4 1 0 (0.750000000 0.250000000)
## 1073422) HouseCosts>=1300 2 0 0 (1.000000000 0.000000000) *
## 1073423) HouseCosts< 1300 2 1 0 (0.500000000 0.500000000)
## 2146846) ElectricBill>=170 1 0 0 (1.000000000 0.000000000) *
## 2146847) ElectricBill< 170 1 0 1 (0.000000000 1.000000000) *
## 67089) ElectricBill< 55 26 1 0 (0.961538462 0.038461538)
## 134178) Insurance< 825 24 0 0 (1.000000000 0.000000000) *
## 134179) Insurance>=825 2 1 0 (0.500000000 0.500000000)
## 268358) Insurance>=875 1 0 0 (1.000000000 0.000000000) *
## 268359) Insurance< 875 1 0 1 (0.000000000 1.000000000) *
## 33545) Insurance>=920 17 1 0 (0.941176471 0.058823529)
## 67090) Insurance>=940 15 0 0 (1.000000000 0.000000000) *
## 67091) Insurance< 940 2 1 0 (0.500000000 0.500000000)
## 134182) HouseCosts< 1300 1 0 0 (1.000000000 0.000000000) *
## 134183) HouseCosts>=1300 1 0 1 (0.000000000 1.000000000) *
## 16773) NumRooms>=10.5 42 2 0 (0.952380952 0.047619048)
## 33546) HouseCosts< 1350 24 0 0 (1.000000000 0.000000000) *
## 33547) HouseCosts>=1350 18 2 0 (0.888888889 0.111111111)
## 67094) HouseCosts>=1650 9 0 0 (1.000000000 0.000000000) *
## 67095) HouseCosts< 1650 9 2 0 (0.777777778 0.222222222)
## 134190) Insurance< 515 5 0 0 (1.000000000 0.000000000) *
## 134191) Insurance>=515 4 2 0 (0.500000000 0.500000000)
## 268382) ElectricBill>=115 2 0 0 (1.000000000 0.000000000) *
## 268383) ElectricBill< 115 2 0 1 (0.000000000 1.000000000) *
## 8387) NumVehicles>=3.5 44 2 0 (0.954545455 0.045454545)
## 16774) NumWorkers>=1.5 42 1 0 (0.976190476 0.023809524)
## 33548) HouseCosts>=1150 31 0 0 (1.000000000 0.000000000) *
## 33549) HouseCosts< 1150 11 1 0 (0.909090909 0.090909091)
## 67098) NumRooms< 9.5 7 0 0 (1.000000000 0.000000000) *
## 67099) NumRooms>=9.5 4 1 0 (0.750000000 0.250000000)
## 134198) ElectricBill>=140 2 0 0 (1.000000000 0.000000000) *
## 134199) ElectricBill< 140 2 1 0 (0.500000000 0.500000000)
## 268398) ElectricBill< 95 1 0 0 (1.000000000 0.000000000) *
## 268399) ElectricBill>=95 1 0 1 (0.000000000 1.000000000) *
## 16775) NumWorkers< 1.5 2 1 0 (0.500000000 0.500000000)
## 33550) Insurance>=675 1 0 0 (1.000000000 0.000000000) *
## 33551) Insurance< 675 1 0 1 (0.000000000 1.000000000) *
## 2097) HouseCosts>=1850 30 2 0 (0.933333333 0.066666667)
## 4194) ElectricBill>=110 18 0 0 (1.000000000 0.000000000) *
## 4195) ElectricBill< 110 12 2 0 (0.833333333 0.166666667)
## 8390) Insurance>=175 10 1 0 (0.900000000 0.100000000)
## 16780) NumWorkers>=1.5 7 0 0 (1.000000000 0.000000000) *
## 16781) NumWorkers< 1.5 3 1 0 (0.666666667 0.333333333)
## 33562) Insurance< 650 2 0 0 (1.000000000 0.000000000) *
## 33563) Insurance>=650 1 0 1 (0.000000000 1.000000000) *
## 8391) Insurance< 175 2 1 0 (0.500000000 0.500000000)
## 16782) NumBedrooms>=3.5 1 0 0 (1.000000000 0.000000000) *
## 16783) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 1049) NumBedrooms>=4.5 103 6 0 (0.941747573 0.058252427)
## 2098) NumRooms< 9.5 48 0 0 (1.000000000 0.000000000) *
## 2099) NumRooms>=9.5 55 6 0 (0.890909091 0.109090909)
## 4198) NumVehicles< 2.5 32 1 0 (0.968750000 0.031250000)
## 8396) OwnRent=Mortgage 30 0 0 (1.000000000 0.000000000) *
## 8397) OwnRent=Rented 2 1 0 (0.500000000 0.500000000)
## 16794) ElectricBill< 76 1 0 0 (1.000000000 0.000000000) *
## 16795) ElectricBill>=76 1 0 1 (0.000000000 1.000000000) *
## 4199) NumVehicles>=2.5 23 5 0 (0.782608696 0.217391304)
## 8398) NumChildren< 3 22 4 0 (0.818181818 0.181818182)
## 16796) NumPeople>=3.5 9 0 0 (1.000000000 0.000000000) *
## 16797) NumPeople< 3.5 13 4 0 (0.692307692 0.307692308)
## 33594) HouseCosts< 1250 8 1 0 (0.875000000 0.125000000)
## 67188) ElectricBill>=70 7 0 0 (1.000000000 0.000000000) *
## 67189) ElectricBill< 70 1 0 1 (0.000000000 1.000000000) *
## 33595) HouseCosts>=1250 5 2 1 (0.400000000 0.600000000)
## 67190) Insurance>=825 3 1 0 (0.666666667 0.333333333)
## 134380) NumPeople>=2.5 2 0 0 (1.000000000 0.000000000) *
## 134381) NumPeople< 2.5 1 0 1 (0.000000000 1.000000000) *
## 67191) Insurance< 825 2 0 1 (0.000000000 1.000000000) *
## 8399) NumChildren>=3 1 0 1 (0.000000000 1.000000000) *
## 525) ElectricBill>=185 363 18 0 (0.950413223 0.049586777)
## 1050) NumChildren< 4.5 362 17 0 (0.953038674 0.046961326)
## 2100) NumVehicles< 5.5 359 16 0 (0.955431755 0.044568245)
## 4200) Insurance< 635 211 6 0 (0.971563981 0.028436019)
## 8400) Insurance>=25 147 2 0 (0.986394558 0.013605442)
## 16800) HouseCosts< 1470 90 0 0 (1.000000000 0.000000000) *
## 16801) HouseCosts>=1470 57 2 0 (0.964912281 0.035087719)
## 33602) HouseCosts>=1550 41 0 0 (1.000000000 0.000000000) *
## 33603) HouseCosts< 1550 16 2 0 (0.875000000 0.125000000)
## 67206) Insurance>=550 5 0 0 (1.000000000 0.000000000) *
## 67207) Insurance< 550 11 2 0 (0.818181818 0.181818182)
## 134414) NumRooms>=9.5 4 0 0 (1.000000000 0.000000000) *
## 134415) NumRooms< 9.5 7 2 0 (0.714285714 0.285714286)
## 268830) NumPeople>=5.5 2 0 0 (1.000000000 0.000000000) *
## 268831) NumPeople< 5.5 5 2 0 (0.600000000 0.400000000)
## 537662) Insurance>=450 4 1 0 (0.750000000 0.250000000)
## 1075324) NumChildren< 2 3 0 0 (1.000000000 0.000000000) *
## 1075325) NumChildren>=2 1 0 1 (0.000000000 1.000000000) *
## 537663) Insurance< 450 1 0 1 (0.000000000 1.000000000) *
## 8401) Insurance< 25 64 4 0 (0.937500000 0.062500000)
## 16802) NumPeople>=4.5 24 0 0 (1.000000000 0.000000000) *
## 16803) NumPeople< 4.5 40 4 0 (0.900000000 0.100000000)
## 33606) NumPeople< 3.5 19 0 0 (1.000000000 0.000000000) *
## 33607) NumPeople>=3.5 21 4 0 (0.809523810 0.190476190)
## 67214) HouseCosts< 1650 18 2 0 (0.888888889 0.111111111)
## 134428) ElectricBill>=205 11 0 0 (1.000000000 0.000000000) *
## 134429) ElectricBill< 205 7 2 0 (0.714285714 0.285714286)
## 268858) NumBedrooms< 3.5 4 0 0 (1.000000000 0.000000000) *
## 268859) NumBedrooms>=3.5 3 1 1 (0.333333333 0.666666667)
## 537718) HouseCosts>=1300 1 0 0 (1.000000000 0.000000000) *
## 537719) HouseCosts< 1300 2 0 1 (0.000000000 1.000000000) *
## 67215) HouseCosts>=1650 3 1 1 (0.333333333 0.666666667)
## 134430) ElectricBill>=225 2 1 0 (0.500000000 0.500000000)
## 268860) ElectricBill< 240 1 0 0 (1.000000000 0.000000000) *
## 268861) ElectricBill>=240 1 0 1 (0.000000000 1.000000000) *
## 134431) ElectricBill< 225 1 0 1 (0.000000000 1.000000000) *
## 4201) Insurance>=635 148 10 0 (0.932432432 0.067567568)
## 8402) Insurance>=645 147 9 0 (0.938775510 0.061224490)
## 16804) Insurance>=695 136 7 0 (0.948529412 0.051470588)
## 33608) HouseCosts>=1350 68 1 0 (0.985294118 0.014705882)
## 67216) NumChildren< 2.5 56 0 0 (1.000000000 0.000000000) *
## 67217) NumChildren>=2.5 12 1 0 (0.916666667 0.083333333)
## 134434) Insurance>=795 10 0 0 (1.000000000 0.000000000) *
## 134435) Insurance< 795 2 1 0 (0.500000000 0.500000000)
## 268870) Insurance< 765 1 0 0 (1.000000000 0.000000000) *
## 268871) Insurance>=765 1 0 1 (0.000000000 1.000000000) *
## 33609) HouseCosts< 1350 68 6 0 (0.911764706 0.088235294)
## 67218) NumVehicles< 4.5 66 5 0 (0.924242424 0.075757576)
## 134436) NumPeople< 2.5 17 0 0 (1.000000000 0.000000000) *
## 134437) NumPeople>=2.5 49 5 0 (0.897959184 0.102040816)
## 268874) NumPeople>=4.5 15 0 0 (1.000000000 0.000000000) *
## 268875) NumPeople< 4.5 34 5 0 (0.852941176 0.147058824)
## 537750) Insurance< 895 28 3 0 (0.892857143 0.107142857)
## 1075500) ElectricBill>=195 26 2 0 (0.923076923 0.076923077)
## 2151000) NumChildren>=0.5 15 0 0 (1.000000000 0.000000000) *
## 2151001) NumChildren< 0.5 11 2 0 (0.818181818 0.181818182)
## 4302002) NumVehicles>=3.5 3 0 0 (1.000000000 0.000000000) *
## 4302003) NumVehicles< 3.5 8 2 0 (0.750000000 0.250000000)
## 8604006) ElectricBill>=250 6 1 0 (0.833333333 0.166666667)
## 17208012) NumRooms< 8.5 4 0 0 (1.000000000 0.000000000) *
## 17208013) NumRooms>=8.5 2 1 0 (0.500000000 0.500000000)
## 34416026) Insurance>=750 1 0 0 (1.000000000 0.000000000) *
## 34416027) Insurance< 750 1 0 1 (0.000000000 1.000000000) *
## 8604007) ElectricBill< 250 2 1 0 (0.500000000 0.500000000)
## 17208014) Insurance>=845 1 0 0 (1.000000000 0.000000000) *
## 17208015) Insurance< 845 1 0 1 (0.000000000 1.000000000) *
## 1075501) ElectricBill< 195 2 1 0 (0.500000000 0.500000000)
## 2151002) HouseCosts< 1200 1 0 0 (1.000000000 0.000000000) *
## 2151003) HouseCosts>=1200 1 0 1 (0.000000000 1.000000000) *
## 537751) Insurance>=895 6 2 0 (0.666666667 0.333333333)
## 1075502) ElectricBill< 215 3 0 0 (1.000000000 0.000000000) *
## 1075503) ElectricBill>=215 3 1 1 (0.333333333 0.666666667)
## 2151006) Insurance>=925 1 0 0 (1.000000000 0.000000000) *
## 2151007) Insurance< 925 2 0 1 (0.000000000 1.000000000) *
## 67219) NumVehicles>=4.5 2 1 0 (0.500000000 0.500000000)
## 134438) Insurance< 850 1 0 0 (1.000000000 0.000000000) *
## 134439) Insurance>=850 1 0 1 (0.000000000 1.000000000) *
## 16805) Insurance< 695 11 2 0 (0.818181818 0.181818182)
## 33610) Insurance< 685 10 1 0 (0.900000000 0.100000000)
## 67220) NumBedrooms>=3.5 8 0 0 (1.000000000 0.000000000) *
## 67221) NumBedrooms< 3.5 2 1 0 (0.500000000 0.500000000)
## 134442) Insurance< 670 1 0 0 (1.000000000 0.000000000) *
## 134443) Insurance>=670 1 0 1 (0.000000000 1.000000000) *
## 33611) Insurance>=685 1 0 1 (0.000000000 1.000000000) *
## 8403) Insurance< 645 1 0 1 (0.000000000 1.000000000) *
## 2101) NumVehicles>=5.5 3 1 0 (0.666666667 0.333333333)
## 4202) Insurance< 790 2 0 0 (1.000000000 0.000000000) *
## 4203) Insurance>=790 1 0 1 (0.000000000 1.000000000) *
## 1051) NumChildren>=4.5 1 0 1 (0.000000000 1.000000000) *
## 263) ElectricBill>=395 42 6 0 (0.857142857 0.142857143)
## 526) NumRooms< 17 40 4 0 (0.900000000 0.100000000)
## 1052) HouseCosts>=1450 17 0 0 (1.000000000 0.000000000) *
## 1053) HouseCosts< 1450 23 4 0 (0.826086957 0.173913043)
## 2106) NumRooms>=9.5 11 0 0 (1.000000000 0.000000000) *
## 2107) NumRooms< 9.5 12 4 0 (0.666666667 0.333333333)
## 4214) HouseCosts< 1200 7 1 0 (0.857142857 0.142857143)
## 8428) NumPeople>=3.5 5 0 0 (1.000000000 0.000000000) *
## 8429) NumPeople< 3.5 2 1 0 (0.500000000 0.500000000)
## 16858) Insurance>=765 1 0 0 (1.000000000 0.000000000) *
## 16859) Insurance< 765 1 0 1 (0.000000000 1.000000000) *
## 4215) HouseCosts>=1200 5 2 1 (0.400000000 0.600000000)
## 8430) NumPeople< 3.5 2 0 0 (1.000000000 0.000000000) *
## 8431) NumPeople>=3.5 3 0 1 (0.000000000 1.000000000) *
## 527) NumRooms>=17 2 0 1 (0.000000000 1.000000000) *
## 33) OwnRent=Outright 100 11 0 (0.890000000 0.110000000)
## 66) NumBedrooms< 2.5 63 3 0 (0.952380952 0.047619048)
## 132) Insurance< 765 59 1 0 (0.983050847 0.016949153)
## 264) Insurance>=75 51 0 0 (1.000000000 0.000000000) *
## 265) Insurance< 75 8 1 0 (0.875000000 0.125000000)
## 530) ElectricBill>=70 7 0 0 (1.000000000 0.000000000) *
## 531) ElectricBill< 70 1 0 1 (0.000000000 1.000000000) *
## 133) Insurance>=765 4 2 0 (0.500000000 0.500000000)
## 266) ElectricBill< 255 2 0 0 (1.000000000 0.000000000) *
## 267) ElectricBill>=255 2 0 1 (0.000000000 1.000000000) *
## 67) NumBedrooms>=2.5 37 8 0 (0.783783784 0.216216216)
## 134) NumVehicles< 1.5 14 0 0 (1.000000000 0.000000000) *
## 135) NumVehicles>=1.5 23 8 0 (0.652173913 0.347826087)
## 270) ElectricBill< 65 6 0 0 (1.000000000 0.000000000) *
## 271) ElectricBill>=65 17 8 0 (0.529411765 0.470588235)
## 542) Insurance>=315 14 5 0 (0.642857143 0.357142857)
## 1084) NumWorkers< 0.5 5 0 0 (1.000000000 0.000000000) *
## 1085) NumWorkers>=0.5 9 4 1 (0.444444444 0.555555556)
## 2170) NumVehicles>=2.5 3 0 0 (1.000000000 0.000000000) *
## 2171) NumVehicles< 2.5 6 1 1 (0.166666667 0.833333333)
## 4342) FoodStamp=Yes 1 0 0 (1.000000000 0.000000000) *
## 4343) FoodStamp=No 5 0 1 (0.000000000 1.000000000) *
## 543) Insurance< 315 3 0 1 (0.000000000 1.000000000) *
## 17) Insurance>=995 2669 119 0 (0.955414013 0.044585987)
## 34) NumRooms< 8.5 2064 64 0 (0.968992248 0.031007752)
## 68) Insurance< 1850 2022 59 0 (0.970820969 0.029179031)
## 136) NumWorkers< 2.5 1651 38 0 (0.976983646 0.023016354)
## 272) HouseCosts>=40 1647 37 0 (0.977534912 0.022465088)
## 544) HouseCosts< 1795 1426 26 0 (0.981767181 0.018232819)
## 1088) NumVehicles< 2.5 1138 16 0 (0.985940246 0.014059754)
## 2176) NumRooms< 7.5 899 8 0 (0.991101224 0.008898776)
## 4352) NumBedrooms< 4.5 893 7 0 (0.992161254 0.007838746)
## 8704) NumChildren< 3.5 882 6 0 (0.993197279 0.006802721)
## 17408) ElectricBill< 235 727 2 0 (0.997248968 0.002751032)
## 34816) NumBedrooms>=2.5 573 0 0 (1.000000000 0.000000000) *
## 34817) NumBedrooms< 2.5 154 2 0 (0.987012987 0.012987013)
## 69634) NumRooms< 5.5 114 0 0 (1.000000000 0.000000000) *
## 69635) NumRooms>=5.5 40 2 0 (0.950000000 0.050000000)
## 139270) HouseCosts< 1300 26 0 0 (1.000000000 0.000000000) *
## 139271) HouseCosts>=1300 14 2 0 (0.857142857 0.142857143)
## 278542) HouseCosts>=1550 9 0 0 (1.000000000 0.000000000) *
## 278543) HouseCosts< 1550 5 2 0 (0.600000000 0.400000000)
## 557086) Insurance< 1150 3 0 0 (1.000000000 0.000000000) *
## 557087) Insurance>=1150 2 0 1 (0.000000000 1.000000000) *
## 17409) ElectricBill>=235 155 4 0 (0.974193548 0.025806452)
## 34818) HouseCosts>=590 134 1 0 (0.992537313 0.007462687)
## 69636) Insurance< 1550 113 0 0 (1.000000000 0.000000000) *
## 69637) Insurance>=1550 21 1 0 (0.952380952 0.047619048)
## 139274) HouseCosts< 1350 16 0 0 (1.000000000 0.000000000) *
## 139275) HouseCosts>=1350 5 1 0 (0.800000000 0.200000000)
## 278550) Insurance>=1650 4 0 0 (1.000000000 0.000000000) *
## 278551) Insurance< 1650 1 0 1 (0.000000000 1.000000000) *
## 34819) HouseCosts< 590 21 3 0 (0.857142857 0.142857143)
## 69638) ElectricBill>=260 19 1 0 (0.947368421 0.052631579)
## 139276) NumBedrooms< 3.5 16 0 0 (1.000000000 0.000000000) *
## 139277) NumBedrooms>=3.5 3 1 0 (0.666666667 0.333333333)
## 278554) Insurance< 1150 2 0 0 (1.000000000 0.000000000) *
## 278555) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 69639) ElectricBill< 260 2 0 1 (0.000000000 1.000000000) *
## 8705) NumChildren>=3.5 11 1 0 (0.909090909 0.090909091)
## 17410) ElectricBill>=165 8 0 0 (1.000000000 0.000000000) *
## 17411) ElectricBill< 165 3 1 0 (0.666666667 0.333333333)
## 34822) Insurance< 1150 2 0 0 (1.000000000 0.000000000) *
## 34823) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 4353) NumBedrooms>=4.5 6 1 0 (0.833333333 0.166666667)
## 8706) ElectricBill>=140 5 0 0 (1.000000000 0.000000000) *
## 8707) ElectricBill< 140 1 0 1 (0.000000000 1.000000000) *
## 2177) NumRooms>=7.5 239 8 0 (0.966527197 0.033472803)
## 4354) NumBedrooms>=2.5 235 7 0 (0.970212766 0.029787234)
## 8708) Insurance< 1750 227 6 0 (0.973568282 0.026431718)
## 17416) HouseCosts>=175 215 5 0 (0.976744186 0.023255814)
## 34832) HouseCosts< 1150 107 1 0 (0.990654206 0.009345794)
## 69664) Insurance>=1050 82 0 0 (1.000000000 0.000000000) *
## 69665) Insurance< 1050 25 1 0 (0.960000000 0.040000000)
## 139330) ElectricBill< 175 20 0 0 (1.000000000 0.000000000) *
## 139331) ElectricBill>=175 5 1 0 (0.800000000 0.200000000)
## 278662) ElectricBill>=190 4 0 0 (1.000000000 0.000000000) *
## 278663) ElectricBill< 190 1 0 1 (0.000000000 1.000000000) *
## 34833) HouseCosts>=1150 108 4 0 (0.962962963 0.037037037)
## 69666) Insurance< 1250 72 1 0 (0.986111111 0.013888889)
## 139332) ElectricBill>=105 55 0 0 (1.000000000 0.000000000) *
## 139333) ElectricBill< 105 17 1 0 (0.941176471 0.058823529)
## 278666) ElectricBill< 95 10 0 0 (1.000000000 0.000000000) *
## 278667) ElectricBill>=95 7 1 0 (0.857142857 0.142857143)
## 557334) HouseCosts>=1350 5 0 0 (1.000000000 0.000000000) *
## 557335) HouseCosts< 1350 2 1 0 (0.500000000 0.500000000)
## 1114670) Insurance>=1100 1 0 0 (1.000000000 0.000000000) *
## 1114671) Insurance< 1100 1 0 1 (0.000000000 1.000000000) *
## 69667) Insurance>=1250 36 3 0 (0.916666667 0.083333333)
## 139334) Insurance>=1450 26 1 0 (0.961538462 0.038461538)
## 278668) HouseCosts>=1250 20 0 0 (1.000000000 0.000000000) *
## 278669) HouseCosts< 1250 6 1 0 (0.833333333 0.166666667)
## 557338) NumBedrooms< 4.5 4 0 0 (1.000000000 0.000000000) *
## 557339) NumBedrooms>=4.5 2 1 0 (0.500000000 0.500000000)
## 1114678) ElectricBill< 115 1 0 0 (1.000000000 0.000000000) *
## 1114679) ElectricBill>=115 1 0 1 (0.000000000 1.000000000) *
## 139335) Insurance< 1450 10 2 0 (0.800000000 0.200000000)
## 278670) ElectricBill>=120 8 1 0 (0.875000000 0.125000000)
## 557340) NumVehicles>=1.5 6 0 0 (1.000000000 0.000000000) *
## 557341) NumVehicles< 1.5 2 1 0 (0.500000000 0.500000000)
## 1114682) Insurance< 1350 1 0 0 (1.000000000 0.000000000) *
## 1114683) Insurance>=1350 1 0 1 (0.000000000 1.000000000) *
## 278671) ElectricBill< 120 2 1 0 (0.500000000 0.500000000)
## 557342) Insurance>=1350 1 0 0 (1.000000000 0.000000000) *
## 557343) Insurance< 1350 1 0 1 (0.000000000 1.000000000) *
## 17417) HouseCosts< 175 12 1 0 (0.916666667 0.083333333)
## 34834) HouseCosts< 145 9 0 0 (1.000000000 0.000000000) *
## 34835) HouseCosts>=145 3 1 0 (0.666666667 0.333333333)
## 69670) Insurance< 1050 2 0 0 (1.000000000 0.000000000) *
## 69671) Insurance>=1050 1 0 1 (0.000000000 1.000000000) *
## 8709) Insurance>=1750 8 1 0 (0.875000000 0.125000000)
## 17418) NumVehicles>=1 7 0 0 (1.000000000 0.000000000) *
## 17419) NumVehicles< 1 1 0 1 (0.000000000 1.000000000) *
## 4355) NumBedrooms< 2.5 4 1 0 (0.750000000 0.250000000)
## 8710) NumWorkers< 1.5 3 0 0 (1.000000000 0.000000000) *
## 8711) NumWorkers>=1.5 1 0 1 (0.000000000 1.000000000) *
## 1089) NumVehicles>=2.5 288 10 0 (0.965277778 0.034722222)
## 2178) NumChildren< 1.5 225 3 0 (0.986666667 0.013333333)
## 4356) HouseCosts>=130 222 2 0 (0.990990991 0.009009009)
## 8712) ElectricBill>=85 204 1 0 (0.995098039 0.004901961)
## 17424) NumChildren< 0.5 162 0 0 (1.000000000 0.000000000) *
## 17425) NumChildren>=0.5 42 1 0 (0.976190476 0.023809524)
## 34850) NumWorkers>=1.5 35 0 0 (1.000000000 0.000000000) *
## 34851) NumWorkers< 1.5 7 1 0 (0.857142857 0.142857143)
## 69702) HouseCosts>=915 5 0 0 (1.000000000 0.000000000) *
## 69703) HouseCosts< 915 2 1 0 (0.500000000 0.500000000)
## 139406) Insurance>=1050 1 0 0 (1.000000000 0.000000000) *
## 139407) Insurance< 1050 1 0 1 (0.000000000 1.000000000) *
## 8713) ElectricBill< 85 18 1 0 (0.944444444 0.055555556)
## 17426) NumBedrooms>=2.5 13 0 0 (1.000000000 0.000000000) *
## 17427) NumBedrooms< 2.5 5 1 0 (0.800000000 0.200000000)
## 34854) HouseCosts< 790 3 0 0 (1.000000000 0.000000000) *
## 34855) HouseCosts>=790 2 1 0 (0.500000000 0.500000000)
## 69710) Insurance< 1100 1 0 0 (1.000000000 0.000000000) *
## 69711) Insurance>=1100 1 0 1 (0.000000000 1.000000000) *
## 4357) HouseCosts< 130 3 1 0 (0.666666667 0.333333333)
## 8714) ElectricBill< 190 2 0 0 (1.000000000 0.000000000) *
## 8715) ElectricBill>=190 1 0 1 (0.000000000 1.000000000) *
## 2179) NumChildren>=1.5 63 7 0 (0.888888889 0.111111111)
## 4358) NumWorkers>=1.5 52 4 0 (0.923076923 0.076923077)
## 8716) ElectricBill>=165 31 0 0 (1.000000000 0.000000000) *
## 8717) ElectricBill< 165 21 4 0 (0.809523810 0.190476190)
## 17434) ElectricBill< 145 16 1 0 (0.937500000 0.062500000)
## 34868) NumVehicles< 3.5 14 0 0 (1.000000000 0.000000000) *
## 34869) NumVehicles>=3.5 2 1 0 (0.500000000 0.500000000)
## 69738) Insurance>=1400 1 0 0 (1.000000000 0.000000000) *
## 69739) Insurance< 1400 1 0 1 (0.000000000 1.000000000) *
## 17435) ElectricBill>=145 5 2 1 (0.400000000 0.600000000)
## 34870) HouseCosts< 1350 2 0 0 (1.000000000 0.000000000) *
## 34871) HouseCosts>=1350 3 0 1 (0.000000000 1.000000000) *
## 4359) NumWorkers< 1.5 11 3 0 (0.727272727 0.272727273)
## 8718) ElectricBill< 160 7 0 0 (1.000000000 0.000000000) *
## 8719) ElectricBill>=160 4 1 1 (0.250000000 0.750000000)
## 17438) HouseCosts>=1300 1 0 0 (1.000000000 0.000000000) *
## 17439) HouseCosts< 1300 3 0 1 (0.000000000 1.000000000) *
## 545) HouseCosts>=1795 221 11 0 (0.950226244 0.049773756)
## 1090) ElectricBill< 555 219 10 0 (0.954337900 0.045662100)
## 2180) ElectricBill>=205 74 0 0 (1.000000000 0.000000000) *
## 2181) ElectricBill< 205 145 10 0 (0.931034483 0.068965517)
## 4362) ElectricBill< 155 94 2 0 (0.978723404 0.021276596)
## 8724) ElectricBill< 135 62 0 0 (1.000000000 0.000000000) *
## 8725) ElectricBill>=135 32 2 0 (0.937500000 0.062500000)
## 17450) Insurance>=1250 16 0 0 (1.000000000 0.000000000) *
## 17451) Insurance< 1250 16 2 0 (0.875000000 0.125000000)
## 34902) NumPeople>=3.5 9 0 0 (1.000000000 0.000000000) *
## 34903) NumPeople< 3.5 7 2 0 (0.714285714 0.285714286)
## 69806) ElectricBill>=145 6 1 0 (0.833333333 0.166666667) *
## 69807) ElectricBill< 145 1 0 1 (0.000000000 1.000000000) *
## 4363) ElectricBill>=155 51 8 0 (0.843137255 0.156862745)
## 8726) ElectricBill>=165 47 6 0 (0.872340426 0.127659574)
## 17452) NumRooms>=3.5 45 5 0 (0.888888889 0.111111111)
## 34904) NumPeople>=2.5 33 2 0 (0.939393939 0.060606061)
## 69808) NumWorkers>=0.5 31 1 0 (0.967741935 0.032258065)
## 139616) NumVehicles< 2.5 19 0 0 (1.000000000 0.000000000) *
## 139617) NumVehicles>=2.5 12 1 0 (0.916666667 0.083333333)
## 279234) ElectricBill< 195 8 0 0 (1.000000000 0.000000000) *
## 279235) ElectricBill>=195 4 1 0 (0.750000000 0.250000000)
## 558470) NumChildren< 1 3 0 0 (1.000000000 0.000000000) *
## 558471) NumChildren>=1 1 0 1 (0.000000000 1.000000000) *
## 69809) NumWorkers< 0.5 2 1 0 (0.500000000 0.500000000)
## 139618) Insurance>=1550 1 0 0 (1.000000000 0.000000000) *
## 139619) Insurance< 1550 1 0 1 (0.000000000 1.000000000) *
## 34905) NumPeople< 2.5 12 3 0 (0.750000000 0.250000000)
## 69810) Insurance>=1450 5 0 0 (1.000000000 0.000000000) *
## 69811) Insurance< 1450 7 3 0 (0.571428571 0.428571429)
## 139622) ElectricBill>=195 2 0 0 (1.000000000 0.000000000) *
## 139623) ElectricBill< 195 5 2 1 (0.400000000 0.600000000)
## 279246) HouseCosts>=1850 3 1 0 (0.666666667 0.333333333)
## 558492) ElectricBill< 185 2 0 0 (1.000000000 0.000000000) *
## 558493) ElectricBill>=185 1 0 1 (0.000000000 1.000000000) *
## 279247) HouseCosts< 1850 2 0 1 (0.000000000 1.000000000) *
## 17453) NumRooms< 3.5 2 1 0 (0.500000000 0.500000000)
## 34906) Insurance< 1300 1 0 0 (1.000000000 0.000000000) *
## 34907) Insurance>=1300 1 0 1 (0.000000000 1.000000000) *
## 8727) ElectricBill< 165 4 2 0 (0.500000000 0.500000000)
## 17454) NumChildren< 0.5 2 0 0 (1.000000000 0.000000000) *
## 17455) NumChildren>=0.5 2 0 1 (0.000000000 1.000000000) *
## 1091) ElectricBill>=555 2 1 0 (0.500000000 0.500000000)
## 2182) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 2183) NumBedrooms>=3.5 1 0 1 (0.000000000 1.000000000) *
## 273) HouseCosts< 40 4 1 0 (0.750000000 0.250000000)
## 546) Insurance>=1050 3 0 0 (1.000000000 0.000000000) *
## 547) Insurance< 1050 1 0 1 (0.000000000 1.000000000) *
## 137) NumWorkers>=2.5 371 21 0 (0.943396226 0.056603774)
## 274) NumRooms>=5.5 322 14 0 (0.956521739 0.043478261)
## 548) NumVehicles< 3.5 230 6 0 (0.973913043 0.026086957)
## 1096) ElectricBill< 235 155 1 0 (0.993548387 0.006451613)
## 2192) Insurance< 1750 147 0 0 (1.000000000 0.000000000) *
## 2193) Insurance>=1750 8 1 0 (0.875000000 0.125000000)
## 4386) ElectricBill>=155 5 0 0 (1.000000000 0.000000000) *
## 4387) ElectricBill< 155 3 1 0 (0.666666667 0.333333333)
## 8774) ElectricBill< 125 2 0 0 (1.000000000 0.000000000) *
## 8775) ElectricBill>=125 1 0 1 (0.000000000 1.000000000) *
## 1097) ElectricBill>=235 75 5 0 (0.933333333 0.066666667)
## 2194) ElectricBill>=245 69 3 0 (0.956521739 0.043478261)
## 4388) ElectricBill< 475 64 2 0 (0.968750000 0.031250000)
## 8776) NumBedrooms< 4.5 59 1 0 (0.983050847 0.016949153)
## 17552) Insurance>=1050 45 0 0 (1.000000000 0.000000000) *
## 17553) Insurance< 1050 14 1 0 (0.928571429 0.071428571)
## 35106) NumRooms>=6.5 11 0 0 (1.000000000 0.000000000) *
## 35107) NumRooms< 6.5 3 1 0 (0.666666667 0.333333333)
## 70214) ElectricBill< 290 2 0 0 (1.000000000 0.000000000) *
## 70215) ElectricBill>=290 1 0 1 (0.000000000 1.000000000) *
## 8777) NumBedrooms>=4.5 5 1 0 (0.800000000 0.200000000)
## 17554) ElectricBill>=275 4 0 0 (1.000000000 0.000000000) *
## 17555) ElectricBill< 275 1 0 1 (0.000000000 1.000000000) *
## 4389) ElectricBill>=475 5 1 0 (0.800000000 0.200000000)
## 8778) Insurance< 1350 4 0 0 (1.000000000 0.000000000) *
## 8779) Insurance>=1350 1 0 1 (0.000000000 1.000000000) *
## 2195) ElectricBill< 245 6 2 0 (0.666666667 0.333333333)
## 4390) NumPeople< 4.5 3 0 0 (1.000000000 0.000000000) *
## 4391) NumPeople>=4.5 3 1 1 (0.333333333 0.666666667)
## 8782) NumPeople>=5.5 1 0 0 (1.000000000 0.000000000) *
## 8783) NumPeople< 5.5 2 0 1 (0.000000000 1.000000000) *
## 549) NumVehicles>=3.5 92 8 0 (0.913043478 0.086956522)
## 1098) Insurance< 1450 73 4 0 (0.945205479 0.054794521)
## 2196) Insurance>=1150 38 0 0 (1.000000000 0.000000000) *
## 2197) Insurance< 1150 35 4 0 (0.885714286 0.114285714)
## 4394) NumVehicles< 4.5 30 2 0 (0.933333333 0.066666667)
## 8788) ElectricBill>=95 27 1 0 (0.962962963 0.037037037)
## 17576) HouseCosts>=640 23 0 0 (1.000000000 0.000000000) *
## 17577) HouseCosts< 640 4 1 0 (0.750000000 0.250000000)
## 35154) HouseCosts< 590 3 0 0 (1.000000000 0.000000000) *
## 35155) HouseCosts>=590 1 0 1 (0.000000000 1.000000000) *
## 8789) ElectricBill< 95 3 1 0 (0.666666667 0.333333333)
## 17578) HouseCosts< 1010 2 0 0 (1.000000000 0.000000000) *
## 17579) HouseCosts>=1010 1 0 1 (0.000000000 1.000000000) *
## 4395) NumVehicles>=4.5 5 2 0 (0.600000000 0.400000000)
## 8790) NumBedrooms< 3.5 3 0 0 (1.000000000 0.000000000) *
## 8791) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 1099) Insurance>=1450 19 4 0 (0.789473684 0.210526316)
## 2198) ElectricBill>=115 18 3 0 (0.833333333 0.166666667)
## 4396) ElectricBill>=195 12 1 0 (0.916666667 0.083333333)
## 8792) HouseCosts>=820 9 0 0 (1.000000000 0.000000000) *
## 8793) HouseCosts< 820 3 1 0 (0.666666667 0.333333333)
## 17586) HouseCosts< 750 2 0 0 (1.000000000 0.000000000) *
## 17587) HouseCosts>=750 1 0 1 (0.000000000 1.000000000) *
## 4397) ElectricBill< 195 6 2 0 (0.666666667 0.333333333)
## 8794) ElectricBill< 165 3 0 0 (1.000000000 0.000000000) *
## 8795) ElectricBill>=165 3 1 1 (0.333333333 0.666666667)
## 17590) HouseCosts< 590 1 0 0 (1.000000000 0.000000000) *
## 17591) HouseCosts>=590 2 0 1 (0.000000000 1.000000000) *
## 2199) ElectricBill< 115 1 0 1 (0.000000000 1.000000000) *
## 275) NumRooms< 5.5 49 7 0 (0.857142857 0.142857143)
## 550) ElectricBill< 190 30 2 0 (0.933333333 0.066666667)
## 1100) Insurance< 1450 22 0 0 (1.000000000 0.000000000) *
## 1101) Insurance>=1450 8 2 0 (0.750000000 0.250000000)
## 2202) Insurance>=1650 3 0 0 (1.000000000 0.000000000) *
## 2203) Insurance< 1650 5 2 0 (0.600000000 0.400000000)
## 4406) ElectricBill< 120 2 0 0 (1.000000000 0.000000000) *
## 4407) ElectricBill>=120 3 1 1 (0.333333333 0.666666667)
## 8814) ElectricBill>=155 1 0 0 (1.000000000 0.000000000) *
## 8815) ElectricBill< 155 2 0 1 (0.000000000 1.000000000) *
## 551) ElectricBill>=190 19 5 0 (0.736842105 0.263157895)
## 1102) NumChildren>=1.5 6 0 0 (1.000000000 0.000000000) *
## 1103) NumChildren< 1.5 13 5 0 (0.615384615 0.384615385)
## 2206) ElectricBill>=205 9 2 0 (0.777777778 0.222222222)
## 4412) HouseCosts>=1050 8 1 0 (0.875000000 0.125000000)
## 8824) ElectricBill< 330 6 0 0 (1.000000000 0.000000000) *
## 8825) ElectricBill>=330 2 1 0 (0.500000000 0.500000000)
## 17650) Insurance< 1150 1 0 0 (1.000000000 0.000000000) *
## 17651) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 4413) HouseCosts< 1050 1 0 1 (0.000000000 1.000000000) *
## 2207) ElectricBill< 205 4 1 1 (0.250000000 0.750000000)
## 4414) HouseCosts< 850 1 0 0 (1.000000000 0.000000000) *
## 4415) HouseCosts>=850 3 0 1 (0.000000000 1.000000000) *
## 69) Insurance>=1850 42 5 0 (0.880952381 0.119047619)
## 138) NumRooms< 7.5 31 2 0 (0.935483871 0.064516129)
## 276) HouseCosts>=525 29 1 0 (0.965517241 0.034482759)
## 552) NumBedrooms>=2.5 22 0 0 (1.000000000 0.000000000) *
## 553) NumBedrooms< 2.5 7 1 0 (0.857142857 0.142857143)
## 1106) NumPeople>=2.5 4 0 0 (1.000000000 0.000000000) *
## 1107) NumPeople< 2.5 3 1 0 (0.666666667 0.333333333)
## 2214) ElectricBill< 95 2 0 0 (1.000000000 0.000000000) *
## 2215) ElectricBill>=95 1 0 1 (0.000000000 1.000000000) *
## 277) HouseCosts< 525 2 1 0 (0.500000000 0.500000000)
## 554) ElectricBill>=100 1 0 0 (1.000000000 0.000000000) *
## 555) ElectricBill< 100 1 0 1 (0.000000000 1.000000000) *
## 139) NumRooms>=7.5 11 3 0 (0.727272727 0.272727273)
## 278) HouseCosts< 1300 7 0 0 (1.000000000 0.000000000) *
## 279) HouseCosts>=1300 4 1 1 (0.250000000 0.750000000)
## 558) NumVehicles< 1.5 1 0 0 (1.000000000 0.000000000) *
## 559) NumVehicles>=1.5 3 0 1 (0.000000000 1.000000000) *
## 35) NumRooms>=8.5 605 55 0 (0.909090909 0.090909091)
## 70) ElectricBill< 315 522 40 0 (0.923371648 0.076628352)
## 140) HouseCosts>=455 462 31 0 (0.932900433 0.067099567)
## 280) OwnRent=Mortgage 460 30 0 (0.934782609 0.065217391)
## 560) NumVehicles< 3.5 399 22 0 (0.944862155 0.055137845)
## 1120) NumChildren< 1.5 281 10 0 (0.964412811 0.035587189)
## 2240) Insurance< 1750 263 7 0 (0.973384030 0.026615970)
## 4480) Insurance>=1250 117 0 0 (1.000000000 0.000000000) *
## 4481) Insurance< 1250 146 7 0 (0.952054795 0.047945205)
## 8962) HouseCosts< 1270 72 1 0 (0.986111111 0.013888889)
## 17924) NumChildren< 0.5 58 0 0 (1.000000000 0.000000000) *
## 17925) NumChildren>=0.5 14 1 0 (0.928571429 0.071428571)
## 35850) ElectricBill< 165 10 0 0 (1.000000000 0.000000000) *
## 35851) ElectricBill>=165 4 1 0 (0.750000000 0.250000000)
## 71702) ElectricBill>=185 3 0 0 (1.000000000 0.000000000) *
## 71703) ElectricBill< 185 1 0 1 (0.000000000 1.000000000) *
## 8963) HouseCosts>=1270 74 6 0 (0.918918919 0.081081081)
## 17926) NumBedrooms< 3.5 22 0 0 (1.000000000 0.000000000) *
## 17927) NumBedrooms>=3.5 52 6 0 (0.884615385 0.115384615)
## 35854) NumPeople>=2.5 24 1 0 (0.958333333 0.041666667)
## 71708) NumBedrooms< 4.5 17 0 0 (1.000000000 0.000000000) *
## 71709) NumBedrooms>=4.5 7 1 0 (0.857142857 0.142857143)
## 143418) Insurance< 1150 5 0 0 (1.000000000 0.000000000) *
## 143419) Insurance>=1150 2 1 0 (0.500000000 0.500000000)
## 286838) ElectricBill< 190 1 0 0 (1.000000000 0.000000000) *
## 286839) ElectricBill>=190 1 0 1 (0.000000000 1.000000000) *
## 35855) NumPeople< 2.5 28 5 0 (0.821428571 0.178571429)
## 71710) ElectricBill< 95 6 0 0 (1.000000000 0.000000000) *
## 71711) ElectricBill>=95 22 5 0 (0.772727273 0.227272727)
## 143422) ElectricBill>=125 18 2 0 (0.888888889 0.111111111)
## 286844) Insurance>=1050 11 0 0 (1.000000000 0.000000000) *
## 286845) Insurance< 1050 7 2 0 (0.714285714 0.285714286)
## 573690) ElectricBill< 165 4 0 0 (1.000000000 0.000000000) *
## 573691) ElectricBill>=165 3 1 1 (0.333333333 0.666666667)
## 1147382) ElectricBill>=195 1 0 0 (1.000000000 0.000000000) *
## 1147383) ElectricBill< 195 2 0 1 (0.000000000 1.000000000) *
## 143423) ElectricBill< 125 4 1 1 (0.250000000 0.750000000)
## 286846) Insurance< 1100 1 0 0 (1.000000000 0.000000000) *
## 286847) Insurance>=1100 3 0 1 (0.000000000 1.000000000) *
## 2241) Insurance>=1750 18 3 0 (0.833333333 0.166666667)
## 4482) NumRooms< 17 17 2 0 (0.882352941 0.117647059)
## 8964) Insurance>=1850 9 0 0 (1.000000000 0.000000000) *
## 8965) Insurance< 1850 8 2 0 (0.750000000 0.250000000)
## 17930) NumVehicles< 2.5 4 0 0 (1.000000000 0.000000000) *
## 17931) NumVehicles>=2.5 4 2 0 (0.500000000 0.500000000)
## 35862) ElectricBill>=145 3 1 0 (0.666666667 0.333333333)
## 71724) HouseCosts>=990 2 0 0 (1.000000000 0.000000000) *
## 71725) HouseCosts< 990 1 0 1 (0.000000000 1.000000000) *
## 35863) ElectricBill< 145 1 0 1 (0.000000000 1.000000000) *
## 4483) NumRooms>=17 1 0 1 (0.000000000 1.000000000) *
## 1121) NumChildren>=1.5 118 12 0 (0.898305085 0.101694915)
## 2242) ElectricBill< 195 82 5 0 (0.939024390 0.060975610)
## 4484) NumRooms>=9.5 43 0 0 (1.000000000 0.000000000) *
## 4485) NumRooms< 9.5 39 5 0 (0.871794872 0.128205128)
## 8970) NumPeople< 7.5 38 4 0 (0.894736842 0.105263158)
## 17940) HouseCosts>=1150 21 0 0 (1.000000000 0.000000000) *
## 17941) HouseCosts< 1150 17 4 0 (0.764705882 0.235294118)
## 35882) HouseCosts< 985 10 1 0 (0.900000000 0.100000000)
## 71764) ElectricBill< 145 8 0 0 (1.000000000 0.000000000) *
## 71765) ElectricBill>=145 2 1 0 (0.500000000 0.500000000)
## 143530) Insurance>=1050 1 0 0 (1.000000000 0.000000000) *
## 143531) Insurance< 1050 1 0 1 (0.000000000 1.000000000) *
## 35883) HouseCosts>=985 7 3 0 (0.571428571 0.428571429)
## 71766) ElectricBill>=125 4 1 0 (0.750000000 0.250000000)
## 143532) NumWorkers< 1.5 3 0 0 (1.000000000 0.000000000) *
## 143533) NumWorkers>=1.5 1 0 1 (0.000000000 1.000000000) *
## 71767) ElectricBill< 125 3 1 1 (0.333333333 0.666666667)
## 143534) ElectricBill< 80 1 0 0 (1.000000000 0.000000000) *
## 143535) ElectricBill>=80 2 0 1 (0.000000000 1.000000000) *
## 8971) NumPeople>=7.5 1 0 1 (0.000000000 1.000000000) *
## 2243) ElectricBill>=195 36 7 0 (0.805555556 0.194444444)
## 4486) NumChildren< 4.5 35 6 0 (0.828571429 0.171428571)
## 8972) ElectricBill>=215 21 1 0 (0.952380952 0.047619048)
## 17944) NumWorkers< 2.5 16 0 0 (1.000000000 0.000000000) *
## 17945) NumWorkers>=2.5 5 1 0 (0.800000000 0.200000000)
## 35890) NumRooms< 9.5 3 0 0 (1.000000000 0.000000000) *
## 35891) NumRooms>=9.5 2 1 0 (0.500000000 0.500000000)
## 71782) Insurance>=1400 1 0 0 (1.000000000 0.000000000) *
## 71783) Insurance< 1400 1 0 1 (0.000000000 1.000000000) *
## 8973) ElectricBill< 215 14 5 0 (0.642857143 0.357142857)
## 17946) NumPeople>=4.5 7 0 0 (1.000000000 0.000000000) *
## 17947) NumPeople< 4.5 7 2 1 (0.285714286 0.714285714)
## 35894) HouseCosts< 1650 5 2 1 (0.400000000 0.600000000)
## 71788) Insurance< 1050 1 0 0 (1.000000000 0.000000000) *
## 71789) Insurance>=1050 4 1 1 (0.250000000 0.750000000)
## 143578) NumBedrooms>=3.5 1 0 0 (1.000000000 0.000000000) *
## 143579) NumBedrooms< 3.5 3 0 1 (0.000000000 1.000000000) *
## 35895) HouseCosts>=1650 2 0 1 (0.000000000 1.000000000) *
## 4487) NumChildren>=4.5 1 0 1 (0.000000000 1.000000000) *
## 561) NumVehicles>=3.5 61 8 0 (0.868852459 0.131147541)
## 1122) HouseCosts< 1850 58 6 0 (0.896551724 0.103448276)
## 2244) ElectricBill>=40 57 5 0 (0.912280702 0.087719298)
## 4488) HouseCosts>=515 55 4 0 (0.927272727 0.072727273)
## 8976) NumRooms>=9.5 30 0 0 (1.000000000 0.000000000) *
## 8977) NumRooms< 9.5 25 4 0 (0.840000000 0.160000000)
## 17954) HouseCosts< 1450 21 2 0 (0.904761905 0.095238095)
## 35908) ElectricBill< 250 18 1 0 (0.944444444 0.055555556)
## 71816) HouseCosts>=770 12 0 0 (1.000000000 0.000000000) *
## 71817) HouseCosts< 770 6 1 0 (0.833333333 0.166666667)
## 143634) HouseCosts< 755 5 0 0 (1.000000000 0.000000000) *
## 143635) HouseCosts>=755 1 0 1 (0.000000000 1.000000000) *
## 35909) ElectricBill>=250 3 1 0 (0.666666667 0.333333333)
## 71818) ElectricBill>=280 2 0 0 (1.000000000 0.000000000) *
## 71819) ElectricBill< 280 1 0 1 (0.000000000 1.000000000) *
## 17955) HouseCosts>=1450 4 2 0 (0.500000000 0.500000000)
## 35910) ElectricBill>=160 2 0 0 (1.000000000 0.000000000) *
## 35911) ElectricBill< 160 2 0 1 (0.000000000 1.000000000) *
## 4489) HouseCosts< 515 2 1 0 (0.500000000 0.500000000)
## 8978) Insurance< 1300 1 0 0 (1.000000000 0.000000000) *
## 8979) Insurance>=1300 1 0 1 (0.000000000 1.000000000) *
## 2245) ElectricBill< 40 1 0 1 (0.000000000 1.000000000) *
## 1123) HouseCosts>=1850 3 1 1 (0.333333333 0.666666667)
## 2246) Insurance>=1250 1 0 0 (1.000000000 0.000000000) *
## 2247) Insurance< 1250 2 0 1 (0.000000000 1.000000000) *
## 281) OwnRent=Outright 2 1 0 (0.500000000 0.500000000)
## 562) ElectricBill>=190 1 0 0 (1.000000000 0.000000000) *
## 563) ElectricBill< 190 1 0 1 (0.000000000 1.000000000) *
## 141) HouseCosts< 455 60 9 0 (0.850000000 0.150000000)
## 282) Insurance< 1150 18 0 0 (1.000000000 0.000000000) *
## 283) Insurance>=1150 42 9 0 (0.785714286 0.214285714)
## 566) NumBedrooms>=4.5 11 0 0 (1.000000000 0.000000000) *
## 567) NumBedrooms< 4.5 31 9 0 (0.709677419 0.290322581)
## 1134) NumRooms< 9.5 18 3 0 (0.833333333 0.166666667)
## 2268) NumVehicles< 4.5 17 2 0 (0.882352941 0.117647059)
## 4536) ElectricBill< 190 11 0 0 (1.000000000 0.000000000) *
## 4537) ElectricBill>=190 6 2 0 (0.666666667 0.333333333)
## 9074) ElectricBill>=225 5 1 0 (0.800000000 0.200000000)
## 18148) Insurance>=1500 3 0 0 (1.000000000 0.000000000) *
## 18149) Insurance< 1500 2 1 0 (0.500000000 0.500000000)
## 36298) Insurance< 1300 1 0 0 (1.000000000 0.000000000) *
## 36299) Insurance>=1300 1 0 1 (0.000000000 1.000000000) *
## 9075) ElectricBill< 225 1 0 1 (0.000000000 1.000000000) *
## 2269) NumVehicles>=4.5 1 0 1 (0.000000000 1.000000000) *
## 1135) NumRooms>=9.5 13 6 0 (0.538461538 0.461538462)
## 2270) NumRooms>=10.5 7 1 0 (0.857142857 0.142857143)
## 4540) ElectricBill>=90 5 0 0 (1.000000000 0.000000000) *
## 4541) ElectricBill< 90 2 1 0 (0.500000000 0.500000000)
## 9082) ElectricBill< 60 1 0 0 (1.000000000 0.000000000) *
## 9083) ElectricBill>=60 1 0 1 (0.000000000 1.000000000) *
## 2271) NumRooms< 10.5 6 1 1 (0.166666667 0.833333333)
## 4542) NumChildren>=3 1 0 0 (1.000000000 0.000000000) *
## 4543) NumChildren< 3 5 0 1 (0.000000000 1.000000000) *
## 71) ElectricBill>=315 83 15 0 (0.819277108 0.180722892)
## 142) Insurance>=1050 74 11 0 (0.851351351 0.148648649)
## 284) ElectricBill>=325 72 10 0 (0.861111111 0.138888889)
## 568) HouseCosts>=150 70 9 0 (0.871428571 0.128571429)
## 1136) NumVehicles< 5.5 68 8 0 (0.882352941 0.117647059)
## 2272) NumBedrooms>=4.5 22 1 0 (0.954545455 0.045454545)
## 4544) Insurance>=1150 19 0 0 (1.000000000 0.000000000) *
## 4545) Insurance< 1150 3 1 0 (0.666666667 0.333333333)
## 9090) ElectricBill>=355 2 0 0 (1.000000000 0.000000000) *
## 9091) ElectricBill< 355 1 0 1 (0.000000000 1.000000000) *
## 2273) NumBedrooms< 4.5 46 7 0 (0.847826087 0.152173913)
## 4546) HouseCosts< 855 10 0 0 (1.000000000 0.000000000) *
## 4547) HouseCosts>=855 36 7 0 (0.805555556 0.194444444)
## 9094) HouseCosts>=930 32 5 0 (0.843750000 0.156250000)
## 18188) Insurance>=1250 20 1 0 (0.950000000 0.050000000)
## 36376) HouseCosts< 1700 16 0 0 (1.000000000 0.000000000) *
## 36377) HouseCosts>=1700 4 1 0 (0.750000000 0.250000000)
## 72754) Insurance>=1750 3 0 0 (1.000000000 0.000000000) *
## 72755) Insurance< 1750 1 0 1 (0.000000000 1.000000000) *
## 18189) Insurance< 1250 12 4 0 (0.666666667 0.333333333)
## 36378) HouseCosts>=1450 10 2 0 (0.800000000 0.200000000)
## 72756) NumRooms< 12.5 9 1 0 (0.888888889 0.111111111)
## 145512) HouseCosts>=1550 6 0 0 (1.000000000 0.000000000) *
## 145513) HouseCosts< 1550 3 1 0 (0.666666667 0.333333333)
## 291026) ElectricBill>=415 2 0 0 (1.000000000 0.000000000) *
## 291027) ElectricBill< 415 1 0 1 (0.000000000 1.000000000) *
## 72757) NumRooms>=12.5 1 0 1 (0.000000000 1.000000000) *
## 36379) HouseCosts< 1450 2 0 1 (0.000000000 1.000000000) *
## 9095) HouseCosts< 930 4 2 0 (0.500000000 0.500000000)
## 18190) NumChildren>=1.5 2 0 0 (1.000000000 0.000000000) *
## 18191) NumChildren< 1.5 2 0 1 (0.000000000 1.000000000) *
## 1137) NumVehicles>=5.5 2 1 0 (0.500000000 0.500000000)
## 2274) ElectricBill< 405 1 0 0 (1.000000000 0.000000000) *
## 2275) ElectricBill>=405 1 0 1 (0.000000000 1.000000000) *
## 569) HouseCosts< 150 2 1 0 (0.500000000 0.500000000)
## 1138) Insurance>=1550 1 0 0 (1.000000000 0.000000000) *
## 1139) Insurance< 1550 1 0 1 (0.000000000 1.000000000) *
## 285) ElectricBill< 325 2 1 0 (0.500000000 0.500000000)
## 570) Insurance>=1400 1 0 0 (1.000000000 0.000000000) *
## 571) Insurance< 1400 1 0 1 (0.000000000 1.000000000) *
## 143) Insurance< 1050 9 4 0 (0.555555556 0.444444444)
## 286) NumBedrooms>=3.5 8 3 0 (0.625000000 0.375000000)
## 572) NumBedrooms< 4.5 3 0 0 (1.000000000 0.000000000) *
## 573) NumBedrooms>=4.5 5 2 1 (0.400000000 0.600000000)
## 1146) HouseCosts< 1100 3 1 0 (0.666666667 0.333333333)
## 2292) ElectricBill< 365 1 0 0 (1.000000000 0.000000000) *
## 2293) ElectricBill>=365 2 1 0 (0.500000000 0.500000000)
## 4586) ElectricBill>=395 1 0 0 (1.000000000 0.000000000) *
## 4587) ElectricBill< 395 1 0 1 (0.000000000 1.000000000) *
## 1147) HouseCosts>=1100 2 0 1 (0.000000000 1.000000000) *
## 287) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 9) HouseCosts>=1905 3209 237 0 (0.926145217 0.073854783)
## 18) NumRooms< 7.5 1848 78 0 (0.957792208 0.042207792)
## 36) HouseCosts< 2950 1545 52 0 (0.966343042 0.033656958)
## 72) HouseCosts>=1915 1543 51 0 (0.966947505 0.033052495)
## 144) NumVehicles< 1.5 406 4 0 (0.990147783 0.009852217)
## 288) ElectricBill< 165 221 0 0 (1.000000000 0.000000000) *
## 289) ElectricBill>=165 185 4 0 (0.978378378 0.021621622)
## 578) ElectricBill>=185 164 2 0 (0.987804878 0.012195122)
## 1156) Insurance< 1450 127 0 0 (1.000000000 0.000000000) *
## 1157) Insurance>=1450 37 2 0 (0.945945946 0.054054054)
## 2314) NumPeople>=2.5 28 0 0 (1.000000000 0.000000000) *
## 2315) NumPeople< 2.5 9 2 0 (0.777777778 0.222222222)
## 4630) HouseCosts< 2450 6 0 0 (1.000000000 0.000000000) *
## 4631) HouseCosts>=2450 3 1 1 (0.333333333 0.666666667)
## 9262) ElectricBill< 275 2 1 0 (0.500000000 0.500000000)
## 18524) HouseCosts< 2550 1 0 0 (1.000000000 0.000000000) *
## 18525) HouseCosts>=2550 1 0 1 (0.000000000 1.000000000) *
## 9263) ElectricBill>=275 1 0 1 (0.000000000 1.000000000) *
## 579) ElectricBill< 185 21 2 0 (0.904761905 0.095238095)
## 1158) NumRooms< 6.5 19 1 0 (0.947368421 0.052631579)
## 2316) HouseCosts>=2150 15 0 0 (1.000000000 0.000000000) *
## 2317) HouseCosts< 2150 4 1 0 (0.750000000 0.250000000)
## 4634) Insurance< 550 3 0 0 (1.000000000 0.000000000) *
## 4635) Insurance>=550 1 0 1 (0.000000000 1.000000000) *
## 1159) NumRooms>=6.5 2 1 0 (0.500000000 0.500000000)
## 2318) Insurance>=905 1 0 0 (1.000000000 0.000000000) *
## 2319) Insurance< 905 1 0 1 (0.000000000 1.000000000) *
## 145) NumVehicles>=1.5 1137 47 0 (0.958663149 0.041336851)
## 290) NumRooms< 6.5 670 21 0 (0.968656716 0.031343284)
## 580) OwnRent=Mortgage 634 17 0 (0.973186120 0.026813880)
## 1160) NumWorkers< 2.5 506 10 0 (0.980237154 0.019762846)
## 2320) HouseCosts< 2805 487 8 0 (0.983572895 0.016427105)
## 4640) NumChildren< 3.5 479 7 0 (0.985386221 0.014613779)
## 9280) NumVehicles< 2.5 391 4 0 (0.989769821 0.010230179)
## 18560) Insurance>=655 334 2 0 (0.994011976 0.005988024)
## 37120) HouseCosts>=2225 181 0 0 (1.000000000 0.000000000) *
## 37121) HouseCosts< 2225 153 2 0 (0.986928105 0.013071895)
## 74242) ElectricBill< 255 129 1 0 (0.992248062 0.007751938)
## 148484) NumPeople>=2.5 88 0 0 (1.000000000 0.000000000) *
## 148485) NumPeople< 2.5 41 1 0 (0.975609756 0.024390244)
## 296970) HouseCosts< 2165 29 0 0 (1.000000000 0.000000000) *
## 296971) HouseCosts>=2165 12 1 0 (0.916666667 0.083333333)
## 593942) ElectricBill< 135 7 0 0 (1.000000000 0.000000000) *
## 593943) ElectricBill>=135 5 1 0 (0.800000000 0.200000000)
## 1187886) ElectricBill>=175 4 0 0 (1.000000000 0.000000000) *
## 1187887) ElectricBill< 175 1 0 1 (0.000000000 1.000000000) *
## 74243) ElectricBill>=255 24 1 0 (0.958333333 0.041666667)
## 148486) ElectricBill>=270 19 0 0 (1.000000000 0.000000000) *
## 148487) ElectricBill< 270 5 1 0 (0.800000000 0.200000000)
## 296974) HouseCosts>=2050 4 0 0 (1.000000000 0.000000000) *
## 296975) HouseCosts< 2050 1 0 1 (0.000000000 1.000000000) *
## 18561) Insurance< 655 57 2 0 (0.964912281 0.035087719)
## 37122) Insurance< 630 55 1 0 (0.981818182 0.018181818)
## 74244) NumWorkers>=1.5 39 0 0 (1.000000000 0.000000000) *
## 74245) NumWorkers< 1.5 16 1 0 (0.937500000 0.062500000)
## 148490) NumChildren< 1.5 11 0 0 (1.000000000 0.000000000) *
## 148491) NumChildren>=1.5 5 1 0 (0.800000000 0.200000000)
## 296982) Insurance< 102 3 0 0 (1.000000000 0.000000000) *
## 296983) Insurance>=102 2 1 0 (0.500000000 0.500000000)
## 593966) Insurance>=340 1 0 0 (1.000000000 0.000000000) *
## 593967) Insurance< 340 1 0 1 (0.000000000 1.000000000) *
## 37123) Insurance>=630 2 1 0 (0.500000000 0.500000000)
## 74246) ElectricBill< 215 1 0 0 (1.000000000 0.000000000) *
## 74247) ElectricBill>=215 1 0 1 (0.000000000 1.000000000) *
## 9281) NumVehicles>=2.5 88 3 0 (0.965909091 0.034090909)
## 18562) ElectricBill>=85 84 2 0 (0.976190476 0.023809524)
## 37124) Insurance< 1150 48 0 0 (1.000000000 0.000000000) *
## 37125) Insurance>=1150 36 2 0 (0.944444444 0.055555556)
## 74250) ElectricBill< 195 16 0 0 (1.000000000 0.000000000) *
## 74251) ElectricBill>=195 20 2 0 (0.900000000 0.100000000)
## 148502) NumPeople>=3.5 10 0 0 (1.000000000 0.000000000) *
## 148503) NumPeople< 3.5 10 2 0 (0.800000000 0.200000000)
## 297006) HouseCosts< 2100 3 0 0 (1.000000000 0.000000000) *
## 297007) HouseCosts>=2100 7 2 0 (0.714285714 0.285714286)
## 594014) ElectricBill< 295 6 1 0 (0.833333333 0.166666667)
## 1188028) HouseCosts>=2250 5 0 0 (1.000000000 0.000000000) *
## 1188029) HouseCosts< 2250 1 0 1 (0.000000000 1.000000000) *
## 594015) ElectricBill>=295 1 0 1 (0.000000000 1.000000000) *
## 18563) ElectricBill< 85 4 1 0 (0.750000000 0.250000000)
## 37126) Insurance< 1100 3 0 0 (1.000000000 0.000000000) *
## 37127) Insurance>=1100 1 0 1 (0.000000000 1.000000000) *
## 4641) NumChildren>=3.5 8 1 0 (0.875000000 0.125000000)
## 9282) HouseCosts< 2550 7 0 0 (1.000000000 0.000000000) *
## 9283) HouseCosts>=2550 1 0 1 (0.000000000 1.000000000) *
## 2321) HouseCosts>=2805 19 2 0 (0.894736842 0.105263158)
## 4642) HouseCosts>=2815 18 1 0 (0.944444444 0.055555556)
## 9284) Insurance< 1100 12 0 0 (1.000000000 0.000000000) *
## 9285) Insurance>=1100 6 1 0 (0.833333333 0.166666667)
## 18570) NumRooms< 5.5 4 0 0 (1.000000000 0.000000000) *
## 18571) NumRooms>=5.5 2 1 0 (0.500000000 0.500000000)
## 37142) Insurance>=1350 1 0 0 (1.000000000 0.000000000) *
## 37143) Insurance< 1350 1 0 1 (0.000000000 1.000000000) *
## 4643) HouseCosts< 2815 1 0 1 (0.000000000 1.000000000) *
## 1161) NumWorkers>=2.5 128 7 0 (0.945312500 0.054687500)
## 2322) ElectricBill>=55 127 6 0 (0.952755906 0.047244094)
## 4644) ElectricBill< 540 124 5 0 (0.959677419 0.040322581)
## 9288) NumChildren>=0.5 38 0 0 (1.000000000 0.000000000) *
## 9289) NumChildren< 0.5 86 5 0 (0.941860465 0.058139535)
## 18578) Insurance>=300 83 4 0 (0.951807229 0.048192771)
## 37156) NumBedrooms< 3.5 69 2 0 (0.971014493 0.028985507)
## 74312) ElectricBill< 225 46 0 0 (1.000000000 0.000000000) *
## 74313) ElectricBill>=225 23 2 0 (0.913043478 0.086956522)
## 148626) Insurance>=750 21 1 0 (0.952380952 0.047619048)
## 297252) ElectricBill>=235 17 0 0 (1.000000000 0.000000000) *
## 297253) ElectricBill< 235 4 1 0 (0.750000000 0.250000000)
## 594506) HouseCosts< 2300 3 0 0 (1.000000000 0.000000000) *
## 594507) HouseCosts>=2300 1 0 1 (0.000000000 1.000000000) *
## 148627) Insurance< 750 2 1 0 (0.500000000 0.500000000)
## 297254) Insurance< 535 1 0 0 (1.000000000 0.000000000) *
## 297255) Insurance>=535 1 0 1 (0.000000000 1.000000000) *
## 37157) NumBedrooms>=3.5 14 2 0 (0.857142857 0.142857143)
## 74314) NumVehicles>=2.5 9 0 0 (1.000000000 0.000000000) *
## 74315) NumVehicles< 2.5 5 2 0 (0.600000000 0.400000000)
## 148630) NumPeople>=5.5 2 0 0 (1.000000000 0.000000000) *
## 148631) NumPeople< 5.5 3 1 1 (0.333333333 0.666666667)
## 297262) Insurance>=1100 2 1 0 (0.500000000 0.500000000)
## 594524) ElectricBill>=135 1 0 0 (1.000000000 0.000000000) *
## 594525) ElectricBill< 135 1 0 1 (0.000000000 1.000000000) *
## 297263) Insurance< 1100 1 0 1 (0.000000000 1.000000000) *
## 18579) Insurance< 300 3 1 0 (0.666666667 0.333333333)
## 37158) Insurance< 175 2 0 0 (1.000000000 0.000000000) *
## 37159) Insurance>=175 1 0 1 (0.000000000 1.000000000) *
## 4645) ElectricBill>=540 3 1 0 (0.666666667 0.333333333)
## 9290) Insurance>=1300 2 0 0 (1.000000000 0.000000000) *
## 9291) Insurance< 1300 1 0 1 (0.000000000 1.000000000) *
## 2323) ElectricBill< 55 1 0 1 (0.000000000 1.000000000) *
## 581) OwnRent=Rented 36 4 0 (0.888888889 0.111111111)
## 1162) HouseCosts< 2450 28 2 0 (0.928571429 0.071428571)
## 2324) ElectricBill< 225 17 0 0 (1.000000000 0.000000000) *
## 2325) ElectricBill>=225 11 2 0 (0.818181818 0.181818182)
## 4650) ElectricBill>=275 10 1 0 (0.900000000 0.100000000)
## 9300) NumPeople>=3.5 6 0 0 (1.000000000 0.000000000) *
## 9301) NumPeople< 3.5 4 1 0 (0.750000000 0.250000000)
## 18602) ElectricBill>=325 3 0 0 (1.000000000 0.000000000) *
## 18603) ElectricBill< 325 1 0 1 (0.000000000 1.000000000) *
## 4651) ElectricBill< 275 1 0 1 (0.000000000 1.000000000) *
## 1163) HouseCosts>=2450 8 2 0 (0.750000000 0.250000000)
## 2326) NumWorkers>=1.5 7 1 0 (0.857142857 0.142857143)
## 4652) NumVehicles< 2.5 5 0 0 (1.000000000 0.000000000) *
## 4653) NumVehicles>=2.5 2 1 0 (0.500000000 0.500000000)
## 9306) ElectricBill>=200 1 0 0 (1.000000000 0.000000000) *
## 9307) ElectricBill< 200 1 0 1 (0.000000000 1.000000000) *
## 2327) NumWorkers< 1.5 1 0 1 (0.000000000 1.000000000) *
## 291) NumRooms>=6.5 467 26 0 (0.944325482 0.055674518)
## 582) NumVehicles< 5.5 465 25 0 (0.946236559 0.053763441)
## 1164) ElectricBill< 185 230 8 0 (0.965217391 0.034782609)
## 2328) Insurance< 1750 222 7 0 (0.968468468 0.031531532)
## 4656) NumPeople< 3.5 120 2 0 (0.983333333 0.016666667)
## 9312) Insurance< 1250 91 0 0 (1.000000000 0.000000000) *
## 9313) Insurance>=1250 29 2 0 (0.931034483 0.068965517)
## 18626) HouseCosts>=2150 19 0 0 (1.000000000 0.000000000) *
## 18627) HouseCosts< 2150 10 2 0 (0.800000000 0.200000000)
## 37254) ElectricBill< 175 9 1 0 (0.888888889 0.111111111)
## 74508) Insurance>=1350 7 0 0 (1.000000000 0.000000000) *
## 74509) Insurance< 1350 2 1 0 (0.500000000 0.500000000)
## 149018) ElectricBill< 80 1 0 0 (1.000000000 0.000000000) *
## 149019) ElectricBill>=80 1 0 1 (0.000000000 1.000000000) *
## 37255) ElectricBill>=175 1 0 1 (0.000000000 1.000000000) *
## 4657) NumPeople>=3.5 102 5 0 (0.950980392 0.049019608)
## 9314) ElectricBill>=75 96 3 0 (0.968750000 0.031250000)
## 18628) Insurance>=525 74 1 0 (0.986486486 0.013513514)
## 37256) NumChildren< 2.5 60 0 0 (1.000000000 0.000000000) *
## 37257) NumChildren>=2.5 14 1 0 (0.928571429 0.071428571)
## 74514) HouseCosts< 2450 8 0 0 (1.000000000 0.000000000) *
## 74515) HouseCosts>=2450 6 1 0 (0.833333333 0.166666667)
## 149030) HouseCosts>=2550 4 0 0 (1.000000000 0.000000000) *
## 149031) HouseCosts< 2550 2 1 0 (0.500000000 0.500000000)
## 298062) ElectricBill>=165 1 0 0 (1.000000000 0.000000000) *
## 298063) ElectricBill< 165 1 0 1 (0.000000000 1.000000000) *
## 18629) Insurance< 525 22 2 0 (0.909090909 0.090909091)
## 37258) Insurance< 450 17 0 0 (1.000000000 0.000000000) *
## 37259) Insurance>=450 5 2 0 (0.600000000 0.400000000)
## 74518) ElectricBill< 160 4 1 0 (0.750000000 0.250000000)
## 149036) HouseCosts>=2050 3 0 0 (1.000000000 0.000000000) *
## 149037) HouseCosts< 2050 1 0 1 (0.000000000 1.000000000) *
## 74519) ElectricBill>=160 1 0 1 (0.000000000 1.000000000) *
## 9315) ElectricBill< 75 6 2 0 (0.666666667 0.333333333)
## 18630) Insurance< 1050 3 0 0 (1.000000000 0.000000000) *
## 18631) Insurance>=1050 3 1 1 (0.333333333 0.666666667)
## 37262) ElectricBill< 45 1 0 0 (1.000000000 0.000000000) *
## 37263) ElectricBill>=45 2 0 1 (0.000000000 1.000000000) *
## 2329) Insurance>=1750 8 1 0 (0.875000000 0.125000000)
## 4658) NumChildren>=0.5 7 0 0 (1.000000000 0.000000000) *
## 4659) NumChildren< 0.5 1 0 1 (0.000000000 1.000000000) *
## 1165) ElectricBill>=185 235 17 0 (0.927659574 0.072340426)
## 2330) ElectricBill>=355 43 0 0 (1.000000000 0.000000000) *
## 2331) ElectricBill< 355 192 17 0 (0.911458333 0.088541667)
## 4662) ElectricBill< 345 181 14 0 (0.922651934 0.077348066)
## 9324) NumVehicles< 3.5 174 12 0 (0.931034483 0.068965517)
## 18648) HouseCosts< 2750 156 9 0 (0.942307692 0.057692308)
## 37296) ElectricBill< 215 43 0 0 (1.000000000 0.000000000) *
## 37297) ElectricBill>=215 113 9 0 (0.920353982 0.079646018)
## 74594) ElectricBill>=225 107 7 0 (0.934579439 0.065420561)
## 149188) Insurance>=1350 26 0 0 (1.000000000 0.000000000) *
## 149189) Insurance< 1350 81 7 0 (0.913580247 0.086419753)
## 298378) HouseCosts>=2550 16 0 0 (1.000000000 0.000000000) *
## 298379) HouseCosts< 2550 65 7 0 (0.892307692 0.107692308)
## 596758) NumPeople>=5.5 10 0 0 (1.000000000 0.000000000) *
## 596759) NumPeople< 5.5 55 7 0 (0.872727273 0.127272727)
## 1193518) NumPeople< 3.5 27 2 0 (0.925925926 0.074074074)
## 2387036) OwnRent=Mortgage 24 1 0 (0.958333333 0.041666667)
## 4774072) NumVehicles< 2.5 18 0 0 (1.000000000 0.000000000) *
## 4774073) NumVehicles>=2.5 6 1 0 (0.833333333 0.166666667)
## 9548146) Insurance< 980 4 0 0 (1.000000000 0.000000000) *
## 9548147) Insurance>=980 2 1 0 (0.500000000 0.500000000)
## 19096294) ElectricBill< 240 1 0 0 (1.000000000 0.000000000) *
## 19096295) ElectricBill>=240 1 0 1 (0.000000000 1.000000000) *
## 2387037) OwnRent=Rented 3 1 0 (0.666666667 0.333333333)
## 4774074) HouseCosts>=2250 2 0 0 (1.000000000 0.000000000) *
## 4774075) HouseCosts< 2250 1 0 1 (0.000000000 1.000000000) *
## 1193519) NumPeople>=3.5 28 5 0 (0.821428571 0.178571429)
## 2387038) HouseCosts< 2450 25 3 0 (0.880000000 0.120000000)
## 4774076) Insurance< 750 7 0 0 (1.000000000 0.000000000) *
## 4774077) Insurance>=750 18 3 0 (0.833333333 0.166666667)
## 9548154) ElectricBill< 295 11 1 0 (0.909090909 0.090909091)
## 19096308) HouseCosts>=2050 8 0 0 (1.000000000 0.000000000) *
## 19096309) HouseCosts< 2050 3 1 0 (0.666666667 0.333333333)
## 38192618) Insurance>=1100 2 0 0 (1.000000000 0.000000000) *
## 38192619) Insurance< 1100 1 0 1 (0.000000000 1.000000000) *
## 9548155) ElectricBill>=295 7 2 0 (0.714285714 0.285714286)
## 19096310) HouseCosts< 2050 4 0 0 (1.000000000 0.000000000) *
## 19096311) HouseCosts>=2050 3 1 1 (0.333333333 0.666666667)
## 38192622) Insurance>=900 2 1 0 (0.500000000 0.500000000)
## 76385244) Insurance< 1100 1 0 0 (1.000000000 0.000000000) *
## 76385245) Insurance>=1100 1 0 1 (0.000000000 1.000000000) *
## 38192623) Insurance< 900 1 0 1 (0.000000000 1.000000000) *
## 2387039) HouseCosts>=2450 3 1 1 (0.333333333 0.666666667)
## 4774078) NumChildren>=2.5 1 0 0 (1.000000000 0.000000000) *
## 4774079) NumChildren< 2.5 2 0 1 (0.000000000 1.000000000) *
## 74595) ElectricBill< 225 6 2 0 (0.666666667 0.333333333)
## 149190) NumBedrooms< 3.5 4 0 0 (1.000000000 0.000000000) *
## 149191) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 18649) HouseCosts>=2750 18 3 0 (0.833333333 0.166666667)
## 37298) ElectricBill>=210 11 0 0 (1.000000000 0.000000000) *
## 37299) ElectricBill< 210 7 3 0 (0.571428571 0.428571429)
## 74598) NumChildren>=1.5 3 0 0 (1.000000000 0.000000000) *
## 74599) NumChildren< 1.5 4 1 1 (0.250000000 0.750000000)
## 149198) Insurance>=610 2 1 0 (0.500000000 0.500000000)
## 298396) Insurance< 1210 1 0 0 (1.000000000 0.000000000) *
## 298397) Insurance>=1210 1 0 1 (0.000000000 1.000000000) *
## 149199) Insurance< 610 2 0 1 (0.000000000 1.000000000) *
## 9325) NumVehicles>=3.5 7 2 0 (0.714285714 0.285714286)
## 18650) ElectricBill>=275 4 0 0 (1.000000000 0.000000000) *
## 18651) ElectricBill< 275 3 1 1 (0.333333333 0.666666667)
## 37302) Insurance>=1300 1 0 0 (1.000000000 0.000000000) *
## 37303) Insurance< 1300 2 0 1 (0.000000000 1.000000000) *
## 4663) ElectricBill>=345 11 3 0 (0.727272727 0.272727273)
## 9326) NumBedrooms< 4.5 10 2 0 (0.800000000 0.200000000)
## 18652) NumVehicles< 2.5 9 1 0 (0.888888889 0.111111111)
## 37304) HouseCosts>=2050 7 0 0 (1.000000000 0.000000000) *
## 37305) HouseCosts< 2050 2 1 0 (0.500000000 0.500000000)
## 74610) Insurance< 900 1 0 0 (1.000000000 0.000000000) *
## 74611) Insurance>=900 1 0 1 (0.000000000 1.000000000) *
## 18653) NumVehicles>=2.5 1 0 1 (0.000000000 1.000000000) *
## 9327) NumBedrooms>=4.5 1 0 1 (0.000000000 1.000000000) *
## 583) NumVehicles>=5.5 2 1 0 (0.500000000 0.500000000)
## 1166) Insurance< 750 1 0 0 (1.000000000 0.000000000) *
## 1167) Insurance>=750 1 0 1 (0.000000000 1.000000000) *
## 73) HouseCosts< 1915 2 1 0 (0.500000000 0.500000000)
## 146) Insurance< 495 1 0 0 (1.000000000 0.000000000) *
## 147) Insurance>=495 1 0 1 (0.000000000 1.000000000) *
## 37) HouseCosts>=2950 303 26 0 (0.914191419 0.085808581)
## 74) NumVehicles< 5.5 302 25 0 (0.917218543 0.082781457)
## 148) Insurance>=115 271 18 0 (0.933579336 0.066420664)
## 296) ElectricBill>=35 268 17 0 (0.936567164 0.063432836)
## 592) ElectricBill< 185 128 5 0 (0.960937500 0.039062500)
## 1184) Insurance>=1150 70 0 0 (1.000000000 0.000000000) *
## 1185) Insurance< 1150 58 5 0 (0.913793103 0.086206897)
## 2370) ElectricBill>=135 29 0 0 (1.000000000 0.000000000) *
## 2371) ElectricBill< 135 29 5 0 (0.827586207 0.172413793)
## 4742) NumVehicles< 1.5 10 0 0 (1.000000000 0.000000000) *
## 4743) NumVehicles>=1.5 19 5 0 (0.736842105 0.263157895)
## 9486) Insurance< 1050 16 3 0 (0.812500000 0.187500000)
## 18972) HouseCosts< 3050 9 0 0 (1.000000000 0.000000000) *
## 18973) HouseCosts>=3050 7 3 0 (0.571428571 0.428571429)
## 37946) NumChildren>=1 2 0 0 (1.000000000 0.000000000) *
## 37947) NumChildren< 1 5 2 1 (0.400000000 0.600000000)
## 75894) Insurance>=840 3 1 0 (0.666666667 0.333333333)
## 151788) Insurance< 990 2 0 0 (1.000000000 0.000000000) *
## 151789) Insurance>=990 1 0 1 (0.000000000 1.000000000) *
## 75895) Insurance< 840 2 0 1 (0.000000000 1.000000000) *
## 9487) Insurance>=1050 3 1 1 (0.333333333 0.666666667)
## 18974) ElectricBill< 110 1 0 0 (1.000000000 0.000000000) *
## 18975) ElectricBill>=110 2 0 1 (0.000000000 1.000000000) *
## 593) ElectricBill>=185 140 12 0 (0.914285714 0.085714286)
## 1186) Insurance< 1550 118 8 0 (0.932203390 0.067796610)
## 2372) NumChildren>=0.5 79 2 0 (0.974683544 0.025316456)
## 4744) ElectricBill< 510 76 1 0 (0.986842105 0.013157895)
## 9488) Insurance< 1450 64 0 0 (1.000000000 0.000000000) *
## 9489) Insurance>=1450 12 1 0 (0.916666667 0.083333333)
## 18978) ElectricBill>=210 11 0 0 (1.000000000 0.000000000) *
## 18979) ElectricBill< 210 1 0 1 (0.000000000 1.000000000) *
## 4745) ElectricBill>=510 3 1 0 (0.666666667 0.333333333)
## 9490) Insurance>=1400 2 0 0 (1.000000000 0.000000000) *
## 9491) Insurance< 1400 1 0 1 (0.000000000 1.000000000) *
## 2373) NumChildren< 0.5 39 6 0 (0.846153846 0.153846154)
## 4746) Insurance>=1050 21 1 0 (0.952380952 0.047619048)
## 9492) NumPeople< 3.5 16 0 0 (1.000000000 0.000000000) *
## 9493) NumPeople>=3.5 5 1 0 (0.800000000 0.200000000)
## 18986) Insurance< 1350 4 0 0 (1.000000000 0.000000000) *
## 18987) Insurance>=1350 1 0 1 (0.000000000 1.000000000) *
## 4747) Insurance< 1050 18 5 0 (0.722222222 0.277777778)
## 9494) ElectricBill>=195 17 4 0 (0.764705882 0.235294118)
## 18988) HouseCosts< 3250 14 2 0 (0.857142857 0.142857143)
## 37976) ElectricBill>=215 12 1 0 (0.916666667 0.083333333)
## 75952) NumBedrooms< 3.5 9 0 0 (1.000000000 0.000000000) *
## 75953) NumBedrooms>=3.5 3 1 0 (0.666666667 0.333333333)
## 151906) Insurance< 855 2 0 0 (1.000000000 0.000000000) *
## 151907) Insurance>=855 1 0 1 (0.000000000 1.000000000) *
## 37977) ElectricBill< 215 2 1 0 (0.500000000 0.500000000)
## 75954) NumBedrooms>=2.5 1 0 0 (1.000000000 0.000000000) *
## 75955) NumBedrooms< 2.5 1 0 1 (0.000000000 1.000000000) *
## 18989) HouseCosts>=3250 3 1 1 (0.333333333 0.666666667)
## 37978) ElectricBill>=305 1 0 0 (1.000000000 0.000000000) *
## 37979) ElectricBill< 305 2 0 1 (0.000000000 1.000000000) *
## 9495) ElectricBill< 195 1 0 1 (0.000000000 1.000000000) *
## 1187) Insurance>=1550 22 4 0 (0.818181818 0.181818182)
## 2374) NumChildren< 1.5 8 0 0 (1.000000000 0.000000000) *
## 2375) NumChildren>=1.5 14 4 0 (0.714285714 0.285714286)
## 4750) NumBedrooms>=3.5 5 0 0 (1.000000000 0.000000000) *
## 4751) NumBedrooms< 3.5 9 4 0 (0.555555556 0.444444444)
## 9502) NumWorkers< 1.5 5 1 0 (0.800000000 0.200000000)
## 19004) ElectricBill>=240 3 0 0 (1.000000000 0.000000000) *
## 19005) ElectricBill< 240 2 1 0 (0.500000000 0.500000000)
## 38010) Insurance< 1750 1 0 0 (1.000000000 0.000000000) *
## 38011) Insurance>=1750 1 0 1 (0.000000000 1.000000000) *
## 9503) NumWorkers>=1.5 4 1 1 (0.250000000 0.750000000)
## 19006) ElectricBill< 215 1 0 0 (1.000000000 0.000000000) *
## 19007) ElectricBill>=215 3 0 1 (0.000000000 1.000000000) *
## 297) ElectricBill< 35 3 1 0 (0.666666667 0.333333333)
## 594) ElectricBill< 15 2 0 0 (1.000000000 0.000000000) *
## 595) ElectricBill>=15 1 0 1 (0.000000000 1.000000000) *
## 149) Insurance< 115 31 7 0 (0.774193548 0.225806452)
## 298) NumBedrooms>=3.5 9 0 0 (1.000000000 0.000000000) *
## 299) NumBedrooms< 3.5 22 7 0 (0.681818182 0.318181818)
## 598) NumRooms< 5.5 7 0 0 (1.000000000 0.000000000) *
## 599) NumRooms>=5.5 15 7 0 (0.533333333 0.466666667)
## 1198) NumVehicles< 1.5 4 0 0 (1.000000000 0.000000000) *
## 1199) NumVehicles>=1.5 11 4 1 (0.363636364 0.636363636)
## 2398) ElectricBill< 175 6 2 0 (0.666666667 0.333333333)
## 4796) NumWorkers< 1.5 5 1 0 (0.800000000 0.200000000)
## 9592) ElectricBill< 105 2 0 0 (1.000000000 0.000000000) *
## 9593) ElectricBill>=105 3 1 0 (0.666666667 0.333333333)
## 19186) HouseCosts>=3100 2 0 0 (1.000000000 0.000000000) *
## 19187) HouseCosts< 3100 1 0 1 (0.000000000 1.000000000) *
## 4797) NumWorkers>=1.5 1 0 1 (0.000000000 1.000000000) *
## 2399) ElectricBill>=175 5 0 1 (0.000000000 1.000000000) *
## 75) NumVehicles>=5.5 1 0 1 (0.000000000 1.000000000) *
## 19) NumRooms>=7.5 1361 159 0 (0.883174137 0.116825863)
## 38) ElectricBill< 285 1054 107 0 (0.898481973 0.101518027)
## 76) NumRooms< 11.5 979 91 0 (0.907048008 0.092951992)
## 152) HouseCosts< 2750 664 48 0 (0.927710843 0.072289157)
## 304) NumVehicles< 4.5 645 44 0 (0.931782946 0.068217054)
## 608) NumRooms< 10.5 611 39 0 (0.936170213 0.063829787)
## 1216) ElectricBill< 75 41 0 0 (1.000000000 0.000000000) *
## 1217) ElectricBill>=75 570 39 0 (0.931578947 0.068421053)
## 2434) ElectricBill>=145 383 22 0 (0.942558747 0.057441253)
## 4868) NumVehicles>=1.5 327 16 0 (0.951070336 0.048929664)
## 9736) NumBedrooms>=2.5 325 15 0 (0.953846154 0.046153846)
## 19472) HouseCosts>=2450 92 1 0 (0.989130435 0.010869565)
## 38944) Insurance>=550 77 0 0 (1.000000000 0.000000000) *
## 38945) Insurance< 550 15 1 0 (0.933333333 0.066666667)
## 77890) Insurance< 450 13 0 0 (1.000000000 0.000000000) *
## 77891) Insurance>=450 2 1 0 (0.500000000 0.500000000)
## 155782) ElectricBill< 175 1 0 0 (1.000000000 0.000000000) *
## 155783) ElectricBill>=175 1 0 1 (0.000000000 1.000000000) *
## 19473) HouseCosts< 2450 233 14 0 (0.939914163 0.060085837)
## 38946) ElectricBill< 225 160 7 0 (0.956250000 0.043750000)
## 77892) NumRooms< 9.5 130 4 0 (0.969230769 0.030769231)
## 155784) Insurance< 1050 57 0 0 (1.000000000 0.000000000) *
## 155785) Insurance>=1050 73 4 0 (0.945205479 0.054794521)
## 311570) NumChildren< 0.5 32 0 0 (1.000000000 0.000000000) *
## 311571) NumChildren>=0.5 41 4 0 (0.902439024 0.097560976)
## 623142) NumPeople>=3.5 30 1 0 (0.966666667 0.033333333)
## 1246284) NumWorkers>=1.5 24 0 0 (1.000000000 0.000000000) *
## 1246285) NumWorkers< 1.5 6 1 0 (0.833333333 0.166666667)
## 2492570) ElectricBill< 195 4 0 0 (1.000000000 0.000000000) *
## 2492571) ElectricBill>=195 2 1 0 (0.500000000 0.500000000)
## 4985142) Insurance>=1350 1 0 0 (1.000000000 0.000000000) *
## 4985143) Insurance< 1350 1 0 1 (0.000000000 1.000000000) *
## 623143) NumPeople< 3.5 11 3 0 (0.727272727 0.272727273)
## 1246286) NumVehicles< 2.5 8 1 0 (0.875000000 0.125000000)
## 2492572) HouseCosts< 2350 6 0 0 (1.000000000 0.000000000) *
## 2492573) HouseCosts>=2350 2 1 0 (0.500000000 0.500000000)
## 4985146) Insurance< 1400 1 0 0 (1.000000000 0.000000000) *
## 4985147) Insurance>=1400 1 0 1 (0.000000000 1.000000000) *
## 1246287) NumVehicles>=2.5 3 1 1 (0.333333333 0.666666667)
## 2492574) Insurance>=1500 1 0 0 (1.000000000 0.000000000) *
## 2492575) Insurance< 1500 2 0 1 (0.000000000 1.000000000) *
## 77893) NumRooms>=9.5 30 3 0 (0.900000000 0.100000000)
## 155786) ElectricBill>=165 23 1 0 (0.956521739 0.043478261)
## 311572) HouseCosts>=2050 19 0 0 (1.000000000 0.000000000) *
## 311573) HouseCosts< 2050 4 1 0 (0.750000000 0.250000000)
## 623146) NumChildren< 1 3 0 0 (1.000000000 0.000000000) *
## 623147) NumChildren>=1 1 0 1 (0.000000000 1.000000000) *
## 155787) ElectricBill< 165 7 2 0 (0.714285714 0.285714286)
## 311574) ElectricBill< 155 4 0 0 (1.000000000 0.000000000) *
## 311575) ElectricBill>=155 3 1 1 (0.333333333 0.666666667)
## 623150) HouseCosts< 2050 1 0 0 (1.000000000 0.000000000) *
## 623151) HouseCosts>=2050 2 0 1 (0.000000000 1.000000000) *
## 38947) ElectricBill>=225 73 7 0 (0.904109589 0.095890411)
## 77894) ElectricBill>=255 20 0 0 (1.000000000 0.000000000) *
## 77895) ElectricBill< 255 53 7 0 (0.867924528 0.132075472)
## 155790) Insurance>=1400 15 0 0 (1.000000000 0.000000000) *
## 155791) Insurance< 1400 38 7 0 (0.815789474 0.184210526)
## 311582) Insurance< 1050 22 2 0 (0.909090909 0.090909091)
## 623164) NumChildren< 2.5 20 1 0 (0.950000000 0.050000000)
## 1246328) NumPeople>=2.5 16 0 0 (1.000000000 0.000000000) *
## 1246329) NumPeople< 2.5 4 1 0 (0.750000000 0.250000000)
## 2492658) Insurance>=955 3 0 0 (1.000000000 0.000000000) *
## 2492659) Insurance< 955 1 0 1 (0.000000000 1.000000000) *
## 623165) NumChildren>=2.5 2 1 0 (0.500000000 0.500000000)
## 1246330) Insurance>=500 1 0 0 (1.000000000 0.000000000) *
## 1246331) Insurance< 500 1 0 1 (0.000000000 1.000000000) *
## 311583) Insurance>=1050 16 5 0 (0.687500000 0.312500000)
## 623166) HouseCosts< 2150 7 0 0 (1.000000000 0.000000000) *
## 623167) HouseCosts>=2150 9 4 1 (0.444444444 0.555555556)
## 1246334) HouseCosts>=2350 4 1 0 (0.750000000 0.250000000)
## 2492668) NumVehicles< 3.5 3 0 0 (1.000000000 0.000000000) *
## 2492669) NumVehicles>=3.5 1 0 1 (0.000000000 1.000000000) *
## 1246335) HouseCosts< 2350 5 1 1 (0.200000000 0.800000000)
## 2492670) ElectricBill< 240 2 1 0 (0.500000000 0.500000000)
## 4985340) HouseCosts< 2250 1 0 0 (1.000000000 0.000000000) *
## 4985341) HouseCosts>=2250 1 0 1 (0.000000000 1.000000000) *
## 2492671) ElectricBill>=240 3 0 1 (0.000000000 1.000000000) *
## 9737) NumBedrooms< 2.5 2 1 0 (0.500000000 0.500000000)
## 19474) Insurance< 1300 1 0 0 (1.000000000 0.000000000) *
## 19475) Insurance>=1300 1 0 1 (0.000000000 1.000000000) *
## 4869) NumVehicles< 1.5 56 6 0 (0.892857143 0.107142857)
## 9738) NumWorkers< 1.5 24 0 0 (1.000000000 0.000000000) *
## 9739) NumWorkers>=1.5 32 6 0 (0.812500000 0.187500000)
## 19478) ElectricBill< 170 9 0 0 (1.000000000 0.000000000) *
## 19479) ElectricBill>=170 23 6 0 (0.739130435 0.260869565)
## 38958) ElectricBill>=195 15 2 0 (0.866666667 0.133333333)
## 77916) HouseCosts< 2450 10 0 0 (1.000000000 0.000000000) *
## 77917) HouseCosts>=2450 5 2 0 (0.600000000 0.400000000)
## 155834) Insurance>=1100 2 0 0 (1.000000000 0.000000000) *
## 155835) Insurance< 1100 3 1 1 (0.333333333 0.666666667)
## 311670) ElectricBill< 225 1 0 0 (1.000000000 0.000000000) *
## 311671) ElectricBill>=225 2 0 1 (0.000000000 1.000000000) *
## 38959) ElectricBill< 195 8 4 0 (0.500000000 0.500000000)
## 77918) NumBedrooms< 3.5 3 0 0 (1.000000000 0.000000000) *
## 77919) NumBedrooms>=3.5 5 1 1 (0.200000000 0.800000000)
## 155838) Insurance>=1350 1 0 0 (1.000000000 0.000000000) *
## 155839) Insurance< 1350 4 0 1 (0.000000000 1.000000000) *
## 2435) ElectricBill< 145 187 17 0 (0.909090909 0.090909091)
## 4870) Insurance< 1650 180 14 0 (0.922222222 0.077777778)
## 9740) NumChildren< 3.5 177 13 0 (0.926553672 0.073446328)
## 19480) ElectricBill>=115 70 2 0 (0.971428571 0.028571429)
## 38960) NumVehicles< 3.5 66 1 0 (0.984848485 0.015151515)
## 77920) NumRooms< 9.5 61 0 0 (1.000000000 0.000000000) *
## 77921) NumRooms>=9.5 5 1 0 (0.800000000 0.200000000)
## 155842) HouseCosts< 2350 4 0 0 (1.000000000 0.000000000) *
## 155843) HouseCosts>=2350 1 0 1 (0.000000000 1.000000000) *
## 38961) NumVehicles>=3.5 4 1 0 (0.750000000 0.250000000)
## 77922) ElectricBill< 125 3 0 0 (1.000000000 0.000000000) *
## 77923) ElectricBill>=125 1 0 1 (0.000000000 1.000000000) *
## 19481) ElectricBill< 115 107 11 0 (0.897196262 0.102803738)
## 38962) HouseCosts< 2650 100 9 0 (0.910000000 0.090000000)
## 77924) NumChildren< 1.5 60 3 0 (0.950000000 0.050000000)
## 155848) NumBedrooms>=3.5 36 0 0 (1.000000000 0.000000000) *
## 155849) NumBedrooms< 3.5 24 3 0 (0.875000000 0.125000000)
## 311698) Insurance>=700 16 1 0 (0.937500000 0.062500000)
## 623396) NumVehicles>=1.5 14 0 0 (1.000000000 0.000000000) *
## 623397) NumVehicles< 1.5 2 1 0 (0.500000000 0.500000000)
## 1246794) Insurance>=1450 1 0 0 (1.000000000 0.000000000) *
## 1246795) Insurance< 1450 1 0 1 (0.000000000 1.000000000) *
## 311699) Insurance< 700 8 2 0 (0.750000000 0.250000000)
## 623398) Insurance< 550 5 0 0 (1.000000000 0.000000000) *
## 623399) Insurance>=550 3 1 1 (0.333333333 0.666666667)
## 1246798) ElectricBill>=105 1 0 0 (1.000000000 0.000000000) *
## 1246799) ElectricBill< 105 2 0 1 (0.000000000 1.000000000) *
## 77925) NumChildren>=1.5 40 6 0 (0.850000000 0.150000000)
## 155850) NumWorkers< 2.5 34 3 0 (0.911764706 0.088235294)
## 311700) ElectricBill< 105 28 1 0 (0.964285714 0.035714286)
## 623400) ElectricBill>=95 17 0 0 (1.000000000 0.000000000) *
## 623401) ElectricBill< 95 11 1 0 (0.909090909 0.090909091)
## 1246802) ElectricBill< 85 8 0 0 (1.000000000 0.000000000) *
## 1246803) ElectricBill>=85 3 1 0 (0.666666667 0.333333333)
## 2493606) Insurance>=1050 2 0 0 (1.000000000 0.000000000) *
## 2493607) Insurance< 1050 1 0 1 (0.000000000 1.000000000) *
## 311701) ElectricBill>=105 6 2 0 (0.666666667 0.333333333)
## 623402) NumChildren>=2.5 3 0 0 (1.000000000 0.000000000) *
## 623403) NumChildren< 2.5 3 1 1 (0.333333333 0.666666667)
## 1246806) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 1246807) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 155851) NumWorkers>=2.5 6 3 0 (0.500000000 0.500000000)
## 311702) NumRooms< 8.5 2 0 0 (1.000000000 0.000000000) *
## 311703) NumRooms>=8.5 4 1 1 (0.250000000 0.750000000)
## 623406) ElectricBill< 85 1 0 0 (1.000000000 0.000000000) *
## 623407) ElectricBill>=85 3 0 1 (0.000000000 1.000000000) *
## 38963) HouseCosts>=2650 7 2 0 (0.714285714 0.285714286)
## 77926) Insurance>=1000 5 0 0 (1.000000000 0.000000000) *
## 77927) Insurance< 1000 2 0 1 (0.000000000 1.000000000) *
## 9741) NumChildren>=3.5 3 1 0 (0.666666667 0.333333333)
## 19482) Insurance< 1150 2 0 0 (1.000000000 0.000000000) *
## 19483) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 4871) Insurance>=1650 7 3 0 (0.571428571 0.428571429)
## 9742) ElectricBill< 115 3 0 0 (1.000000000 0.000000000) *
## 9743) ElectricBill>=115 4 1 1 (0.250000000 0.750000000)
## 19486) HouseCosts< 2050 1 0 0 (1.000000000 0.000000000) *
## 19487) HouseCosts>=2050 3 0 1 (0.000000000 1.000000000) *
## 609) NumRooms>=10.5 34 5 0 (0.852941176 0.147058824)
## 1218) Insurance>=400 26 2 0 (0.923076923 0.076923077)
## 2436) NumBedrooms< 6.5 23 1 0 (0.956521739 0.043478261)
## 4872) NumPeople< 5.5 20 0 0 (1.000000000 0.000000000) *
## 4873) NumPeople>=5.5 3 1 0 (0.666666667 0.333333333)
## 9746) Insurance>=1070 2 0 0 (1.000000000 0.000000000) *
## 9747) Insurance< 1070 1 0 1 (0.000000000 1.000000000) *
## 2437) NumBedrooms>=6.5 3 1 0 (0.666666667 0.333333333)
## 4874) Insurance>=1250 2 0 0 (1.000000000 0.000000000) *
## 4875) Insurance< 1250 1 0 1 (0.000000000 1.000000000) *
## 1219) Insurance< 400 8 3 0 (0.625000000 0.375000000)
## 2438) Insurance< 150 7 2 0 (0.714285714 0.285714286)
## 4876) NumChildren>=0.5 4 0 0 (1.000000000 0.000000000) *
## 4877) NumChildren< 0.5 3 1 1 (0.333333333 0.666666667)
## 9754) NumBedrooms>=4.5 1 0 0 (1.000000000 0.000000000) *
## 9755) NumBedrooms< 4.5 2 0 1 (0.000000000 1.000000000) *
## 2439) Insurance>=150 1 0 1 (0.000000000 1.000000000) *
## 305) NumVehicles>=4.5 19 4 0 (0.789473684 0.210526316)
## 610) Insurance< 770 6 0 0 (1.000000000 0.000000000) *
## 611) Insurance>=770 13 4 0 (0.692307692 0.307692308)
## 1222) Insurance>=1050 8 1 0 (0.875000000 0.125000000)
## 2444) Insurance< 1450 4 0 0 (1.000000000 0.000000000) *
## 2445) Insurance>=1450 4 1 0 (0.750000000 0.250000000)
## 4890) HouseCosts< 2300 2 0 0 (1.000000000 0.000000000) *
## 4891) HouseCosts>=2300 2 1 0 (0.500000000 0.500000000)
## 9782) Insurance>=1650 1 0 0 (1.000000000 0.000000000) *
## 9783) Insurance< 1650 1 0 1 (0.000000000 1.000000000) *
## 1223) Insurance< 1050 5 2 1 (0.400000000 0.600000000)
## 2446) NumBedrooms>=4.5 2 0 0 (1.000000000 0.000000000) *
## 2447) NumBedrooms< 4.5 3 0 1 (0.000000000 1.000000000) *
## 153) HouseCosts>=2750 315 43 0 (0.863492063 0.136507937)
## 306) NumPeople>=2.5 254 28 0 (0.889763780 0.110236220)
## 612) NumVehicles< 2.5 156 12 0 (0.923076923 0.076923077)
## 1224) HouseCosts< 3050 81 3 0 (0.962962963 0.037037037)
## 2448) NumWorkers>=1.5 65 1 0 (0.984615385 0.015384615)
## 4896) Insurance< 1350 46 0 0 (1.000000000 0.000000000) *
## 4897) Insurance>=1350 19 1 0 (0.947368421 0.052631579)
## 9794) Insurance>=1450 13 0 0 (1.000000000 0.000000000) *
## 9795) Insurance< 1450 6 1 0 (0.833333333 0.166666667)
## 19590) NumBedrooms>=3.5 4 0 0 (1.000000000 0.000000000) *
## 19591) NumBedrooms< 3.5 2 1 0 (0.500000000 0.500000000)
## 39182) ElectricBill>=170 1 0 0 (1.000000000 0.000000000) *
## 39183) ElectricBill< 170 1 0 1 (0.000000000 1.000000000) *
## 2449) NumWorkers< 1.5 16 2 0 (0.875000000 0.125000000)
## 4898) ElectricBill< 230 15 1 0 (0.933333333 0.066666667)
## 9796) Insurance>=650 12 0 0 (1.000000000 0.000000000) *
## 9797) Insurance< 650 3 1 0 (0.666666667 0.333333333)
## 19594) Insurance< 300 2 0 0 (1.000000000 0.000000000) *
## 19595) Insurance>=300 1 0 1 (0.000000000 1.000000000) *
## 4899) ElectricBill>=230 1 0 1 (0.000000000 1.000000000) *
## 1225) HouseCosts>=3050 75 9 0 (0.880000000 0.120000000)
## 2450) NumBedrooms< 6.5 71 7 0 (0.901408451 0.098591549)
## 4900) Insurance>=650 58 4 0 (0.931034483 0.068965517)
## 9800) HouseCosts< 3250 35 1 0 (0.971428571 0.028571429)
## 19600) ElectricBill>=105 28 0 0 (1.000000000 0.000000000) *
## 19601) ElectricBill< 105 7 1 0 (0.857142857 0.142857143)
## 39202) NumBedrooms< 4.5 5 0 0 (1.000000000 0.000000000) *
## 39203) NumBedrooms>=4.5 2 1 0 (0.500000000 0.500000000)
## 78406) NumChildren>=1.5 1 0 0 (1.000000000 0.000000000) *
## 78407) NumChildren< 1.5 1 0 1 (0.000000000 1.000000000) *
## 9801) HouseCosts>=3250 23 3 0 (0.869565217 0.130434783)
## 19602) Insurance< 1650 22 2 0 (0.909090909 0.090909091)
## 39204) ElectricBill< 185 13 0 0 (1.000000000 0.000000000) *
## 39205) ElectricBill>=185 9 2 0 (0.777777778 0.222222222)
## 78410) ElectricBill>=195 8 1 0 (0.875000000 0.125000000)
## 156820) NumChildren< 2.5 6 0 0 (1.000000000 0.000000000) *
## 156821) NumChildren>=2.5 2 1 0 (0.500000000 0.500000000)
## 313642) Insurance< 1200 1 0 0 (1.000000000 0.000000000) *
## 313643) Insurance>=1200 1 0 1 (0.000000000 1.000000000) *
## 78411) ElectricBill< 195 1 0 1 (0.000000000 1.000000000) *
## 19603) Insurance>=1650 1 0 1 (0.000000000 1.000000000) *
## 4901) Insurance< 650 13 3 0 (0.769230769 0.230769231)
## 9802) HouseCosts>=3150 9 0 0 (1.000000000 0.000000000) *
## 9803) HouseCosts< 3150 4 1 1 (0.250000000 0.750000000)
## 19606) NumChildren< 0.5 1 0 0 (1.000000000 0.000000000) *
## 19607) NumChildren>=0.5 3 0 1 (0.000000000 1.000000000) *
## 2451) NumBedrooms>=6.5 4 2 0 (0.500000000 0.500000000)
## 4902) Insurance< 900 1 0 0 (1.000000000 0.000000000) *
## 4903) Insurance>=900 3 1 1 (0.333333333 0.666666667)
## 9806) Insurance>=1300 2 1 0 (0.500000000 0.500000000)
## 19612) Insurance< 1550 1 0 0 (1.000000000 0.000000000) *
## 19613) Insurance>=1550 1 0 1 (0.000000000 1.000000000) *
## 9807) Insurance< 1300 1 0 1 (0.000000000 1.000000000) *
## 613) NumVehicles>=2.5 98 16 0 (0.836734694 0.163265306)
## 1226) NumPeople< 9.5 97 15 0 (0.845360825 0.154639175)
## 2452) NumPeople>=3.5 70 8 0 (0.885714286 0.114285714)
## 4904) NumChildren< 2.5 56 4 0 (0.928571429 0.071428571)
## 9808) NumVehicles< 4.5 49 2 0 (0.959183673 0.040816327)
## 19616) ElectricBill>=155 34 0 0 (1.000000000 0.000000000) *
## 19617) ElectricBill< 155 15 2 0 (0.866666667 0.133333333)
## 39234) HouseCosts>=2950 8 0 0 (1.000000000 0.000000000) *
## 39235) HouseCosts< 2950 7 2 0 (0.714285714 0.285714286)
## 78470) ElectricBill< 145 4 0 0 (1.000000000 0.000000000) *
## 78471) ElectricBill>=145 3 1 1 (0.333333333 0.666666667)
## 156942) Insurance< 805 1 0 0 (1.000000000 0.000000000) *
## 156943) Insurance>=805 2 0 1 (0.000000000 1.000000000) *
## 9809) NumVehicles>=4.5 7 2 0 (0.714285714 0.285714286)
## 19618) Insurance>=975 6 1 0 (0.833333333 0.166666667)
## 39236) ElectricBill< 205 3 0 0 (1.000000000 0.000000000) *
## 39237) ElectricBill>=205 3 1 0 (0.666666667 0.333333333)
## 78474) ElectricBill>=230 2 0 0 (1.000000000 0.000000000) *
## 78475) ElectricBill< 230 1 0 1 (0.000000000 1.000000000) *
## 19619) Insurance< 975 1 0 1 (0.000000000 1.000000000) *
## 4905) NumChildren>=2.5 14 4 0 (0.714285714 0.285714286)
## 9810) Insurance< 1450 12 2 0 (0.833333333 0.166666667)
## 19620) NumWorkers< 2.5 9 0 0 (1.000000000 0.000000000) *
## 19621) NumWorkers>=2.5 3 1 1 (0.333333333 0.666666667)
## 39242) ElectricBill>=200 1 0 0 (1.000000000 0.000000000) *
## 39243) ElectricBill< 200 2 0 1 (0.000000000 1.000000000) *
## 9811) Insurance>=1450 2 0 1 (0.000000000 1.000000000) *
## 2453) NumPeople< 3.5 27 7 0 (0.740740741 0.259259259)
## 4906) Insurance>=350 25 5 0 (0.800000000 0.200000000)
## 9812) ElectricBill< 240 24 4 0 (0.833333333 0.166666667)
## 19624) NumChildren>=0.5 9 0 0 (1.000000000 0.000000000) *
## 19625) NumChildren< 0.5 15 4 0 (0.733333333 0.266666667)
## 39250) Insurance>=975 12 2 0 (0.833333333 0.166666667)
## 78500) ElectricBill>=115 10 1 0 (0.900000000 0.100000000)
## 157000) Insurance< 1350 7 0 0 (1.000000000 0.000000000) *
## 157001) Insurance>=1350 3 1 0 (0.666666667 0.333333333)
## 314002) Insurance>=1450 2 0 0 (1.000000000 0.000000000) *
## 314003) Insurance< 1450 1 0 1 (0.000000000 1.000000000) *
## 78501) ElectricBill< 115 2 1 0 (0.500000000 0.500000000)
## 157002) Insurance< 1100 1 0 0 (1.000000000 0.000000000) *
## 157003) Insurance>=1100 1 0 1 (0.000000000 1.000000000) *
## 39251) Insurance< 975 3 1 1 (0.333333333 0.666666667)
## 78502) Insurance>=860 2 1 0 (0.500000000 0.500000000)
## 157004) Insurance< 925 1 0 0 (1.000000000 0.000000000) *
## 157005) Insurance>=925 1 0 1 (0.000000000 1.000000000) *
## 78503) Insurance< 860 1 0 1 (0.000000000 1.000000000) *
## 9813) ElectricBill>=240 1 0 1 (0.000000000 1.000000000) *
## 4907) Insurance< 350 2 0 1 (0.000000000 1.000000000) *
## 1227) NumPeople>=9.5 1 0 1 (0.000000000 1.000000000) *
## 307) NumPeople< 2.5 61 15 0 (0.754098361 0.245901639)
## 614) Insurance< 1650 55 11 0 (0.800000000 0.200000000)
## 1228) HouseCosts>=2850 48 8 0 (0.833333333 0.166666667)
## 2456) HouseCosts< 3065 24 1 0 (0.958333333 0.041666667)
## 4912) NumVehicles< 2.5 21 0 0 (1.000000000 0.000000000) *
## 4913) NumVehicles>=2.5 3 1 0 (0.666666667 0.333333333)
## 9826) Insurance< 1250 2 0 0 (1.000000000 0.000000000) *
## 9827) Insurance>=1250 1 0 1 (0.000000000 1.000000000) *
## 2457) HouseCosts>=3065 24 7 0 (0.708333333 0.291666667)
## 4914) Insurance>=1050 17 3 0 (0.823529412 0.176470588)
## 9828) ElectricBill< 115 7 0 0 (1.000000000 0.000000000) *
## 9829) ElectricBill>=115 10 3 0 (0.700000000 0.300000000)
## 19658) HouseCosts< 3350 9 2 0 (0.777777778 0.222222222)
## 39316) NumRooms< 9.5 8 1 0 (0.875000000 0.125000000)
## 78632) ElectricBill>=125 6 0 0 (1.000000000 0.000000000) *
## 78633) ElectricBill< 125 2 1 0 (0.500000000 0.500000000)
## 157266) Insurance< 1150 1 0 0 (1.000000000 0.000000000) *
## 157267) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 39317) NumRooms>=9.5 1 0 1 (0.000000000 1.000000000) *
## 19659) HouseCosts>=3350 1 0 1 (0.000000000 1.000000000) *
## 4915) Insurance< 1050 7 3 1 (0.428571429 0.571428571)
## 9830) Insurance< 750 5 2 0 (0.600000000 0.400000000)
## 19660) Insurance>=325 2 0 0 (1.000000000 0.000000000) *
## 19661) Insurance< 325 3 1 1 (0.333333333 0.666666667)
## 39322) NumChildren>=0.5 1 0 0 (1.000000000 0.000000000) *
## 39323) NumChildren< 0.5 2 0 1 (0.000000000 1.000000000) *
## 9831) Insurance>=750 2 0 1 (0.000000000 1.000000000) *
## 1229) HouseCosts< 2850 7 3 0 (0.571428571 0.428571429)
## 2458) Insurance< 1450 5 1 0 (0.800000000 0.200000000)
## 4916) ElectricBill< 215 4 0 0 (1.000000000 0.000000000) *
## 4917) ElectricBill>=215 1 0 1 (0.000000000 1.000000000) *
## 2459) Insurance>=1450 2 0 1 (0.000000000 1.000000000) *
## 615) Insurance>=1650 6 2 1 (0.333333333 0.666666667)
## 1230) NumWorkers< 1.5 3 1 0 (0.666666667 0.333333333)
## 2460) ElectricBill< 160 2 0 0 (1.000000000 0.000000000) *
## 2461) ElectricBill>=160 1 0 1 (0.000000000 1.000000000) *
## 1231) NumWorkers>=1.5 3 0 1 (0.000000000 1.000000000) *
## 77) NumRooms>=11.5 75 16 0 (0.786666667 0.213333333)
## 154) ElectricBill>=145 49 7 0 (0.857142857 0.142857143)
## 308) NumPeople< 3.5 17 0 0 (1.000000000 0.000000000) *
## 309) NumPeople>=3.5 32 7 0 (0.781250000 0.218750000)
## 618) NumWorkers>=1.5 29 5 0 (0.827586207 0.172413793)
## 1236) NumVehicles< 2.5 12 0 0 (1.000000000 0.000000000) *
## 1237) NumVehicles>=2.5 17 5 0 (0.705882353 0.294117647)
## 2474) Insurance>=150 16 4 0 (0.750000000 0.250000000)
## 4948) ElectricBill< 245 13 2 0 (0.846153846 0.153846154)
## 9896) Insurance< 1100 8 0 0 (1.000000000 0.000000000) *
## 9897) Insurance>=1100 5 2 0 (0.600000000 0.400000000)
## 19794) Insurance>=1450 2 0 0 (1.000000000 0.000000000) *
## 19795) Insurance< 1450 3 1 1 (0.333333333 0.666666667)
## 39590) ElectricBill>=210 1 0 0 (1.000000000 0.000000000) *
## 39591) ElectricBill< 210 2 0 1 (0.000000000 1.000000000) *
## 4949) ElectricBill>=245 3 1 1 (0.333333333 0.666666667)
## 9898) Insurance>=1100 1 0 0 (1.000000000 0.000000000) *
## 9899) Insurance< 1100 2 0 1 (0.000000000 1.000000000) *
## 2475) Insurance< 150 1 0 1 (0.000000000 1.000000000) *
## 619) NumWorkers< 1.5 3 1 1 (0.333333333 0.666666667)
## 1238) ElectricBill< 185 1 0 0 (1.000000000 0.000000000) *
## 1239) ElectricBill>=185 2 0 1 (0.000000000 1.000000000) *
## 155) ElectricBill< 145 26 9 0 (0.653846154 0.346153846)
## 310) Insurance< 1450 22 6 0 (0.727272727 0.272727273)
## 620) NumChildren>=1.5 10 0 0 (1.000000000 0.000000000) *
## 621) NumChildren< 1.5 12 6 0 (0.500000000 0.500000000)
## 1242) NumChildren< 0.5 6 1 0 (0.833333333 0.166666667)
## 2484) Insurance< 900 4 0 0 (1.000000000 0.000000000) *
## 2485) Insurance>=900 2 1 0 (0.500000000 0.500000000)
## 4970) Insurance>=1150 1 0 0 (1.000000000 0.000000000) *
## 4971) Insurance< 1150 1 0 1 (0.000000000 1.000000000) *
## 1243) NumChildren>=0.5 6 1 1 (0.166666667 0.833333333)
## 2486) Insurance>=1200 1 0 0 (1.000000000 0.000000000) *
## 2487) Insurance< 1200 5 0 1 (0.000000000 1.000000000) *
## 311) Insurance>=1450 4 1 1 (0.250000000 0.750000000)
## 622) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 623) NumBedrooms>=3.5 3 0 1 (0.000000000 1.000000000) *
## 39) ElectricBill>=285 307 52 0 (0.830618893 0.169381107)
## 78) NumPeople>=3.5 221 30 0 (0.864253394 0.135746606)
## 156) NumVehicles< 3.5 166 17 0 (0.897590361 0.102409639)
## 312) Insurance< 1350 107 6 0 (0.943925234 0.056074766)
## 624) NumRooms< 17 105 5 0 (0.952380952 0.047619048)
## 1248) NumChildren< 1.5 37 0 0 (1.000000000 0.000000000) *
## 1249) NumChildren>=1.5 68 5 0 (0.926470588 0.073529412)
## 2498) ElectricBill>=295 66 4 0 (0.939393939 0.060606061)
## 4996) Insurance>=755 44 1 0 (0.977272727 0.022727273)
## 9992) HouseCosts>=2050 36 0 0 (1.000000000 0.000000000) *
## 9993) HouseCosts< 2050 8 1 0 (0.875000000 0.125000000)
## 19986) NumRooms< 9.5 6 0 0 (1.000000000 0.000000000) *
## 19987) NumRooms>=9.5 2 1 0 (0.500000000 0.500000000)
## 39974) Insurance< 1100 1 0 0 (1.000000000 0.000000000) *
## 39975) Insurance>=1100 1 0 1 (0.000000000 1.000000000) *
## 4997) Insurance< 755 22 3 0 (0.863636364 0.136363636)
## 9994) Insurance< 690 21 2 0 (0.904761905 0.095238095)
## 19988) ElectricBill< 435 18 1 0 (0.944444444 0.055555556)
## 39976) ElectricBill>=310 12 0 0 (1.000000000 0.000000000) *
## 39977) ElectricBill< 310 6 1 0 (0.833333333 0.166666667)
## 79954) NumRooms< 9.5 5 0 0 (1.000000000 0.000000000) *
## 79955) NumRooms>=9.5 1 0 1 (0.000000000 1.000000000) *
## 19989) ElectricBill>=435 3 1 0 (0.666666667 0.333333333)
## 39978) Insurance>=2 2 0 0 (1.000000000 0.000000000) *
## 39979) Insurance< 2 1 0 1 (0.000000000 1.000000000) *
## 9995) Insurance>=690 1 0 1 (0.000000000 1.000000000) *
## 2499) ElectricBill< 295 2 1 0 (0.500000000 0.500000000)
## 4998) Insurance< 900 1 0 0 (1.000000000 0.000000000) *
## 4999) Insurance>=900 1 0 1 (0.000000000 1.000000000) *
## 625) NumRooms>=17 2 1 0 (0.500000000 0.500000000)
## 1250) ElectricBill< 435 1 0 0 (1.000000000 0.000000000) *
## 1251) ElectricBill>=435 1 0 1 (0.000000000 1.000000000) *
## 313) Insurance>=1350 59 11 0 (0.813559322 0.186440678)
## 626) NumPeople>=5.5 14 0 0 (1.000000000 0.000000000) *
## 627) NumPeople< 5.5 45 11 0 (0.755555556 0.244444444)
## 1254) HouseCosts>=2350 28 4 0 (0.857142857 0.142857143)
## 2508) ElectricBill< 555 26 3 0 (0.884615385 0.115384615)
## 5016) HouseCosts>=2950 12 0 0 (1.000000000 0.000000000) *
## 5017) HouseCosts< 2950 14 3 0 (0.785714286 0.214285714)
## 10034) NumVehicles< 2.5 9 1 0 (0.888888889 0.111111111)
## 20068) NumBedrooms< 4.5 8 0 0 (1.000000000 0.000000000) *
## 20069) NumBedrooms>=4.5 1 0 1 (0.000000000 1.000000000) *
## 10035) NumVehicles>=2.5 5 2 0 (0.600000000 0.400000000)
## 20070) NumPeople>=4.5 3 0 0 (1.000000000 0.000000000) *
## 20071) NumPeople< 4.5 2 0 1 (0.000000000 1.000000000) *
## 2509) ElectricBill>=555 2 1 0 (0.500000000 0.500000000)
## 5018) HouseCosts< 2900 1 0 0 (1.000000000 0.000000000) *
## 5019) HouseCosts>=2900 1 0 1 (0.000000000 1.000000000) *
## 1255) HouseCosts< 2350 17 7 0 (0.588235294 0.411764706)
## 2510) HouseCosts< 2250 10 2 0 (0.800000000 0.200000000)
## 5020) NumRooms< 9.5 9 1 0 (0.888888889 0.111111111)
## 10040) NumChildren< 2.5 7 0 0 (1.000000000 0.000000000) *
## 10041) NumChildren>=2.5 2 1 0 (0.500000000 0.500000000)
## 20082) Insurance>=1750 1 0 0 (1.000000000 0.000000000) *
## 20083) Insurance< 1750 1 0 1 (0.000000000 1.000000000) *
## 5021) NumRooms>=9.5 1 0 1 (0.000000000 1.000000000) *
## 2511) HouseCosts>=2250 7 2 1 (0.285714286 0.714285714)
## 5022) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 5023) NumBedrooms>=3.5 6 1 1 (0.166666667 0.833333333)
## 10046) NumBedrooms>=6.5 2 1 0 (0.500000000 0.500000000)
## 20092) Insurance< 1550 1 0 0 (1.000000000 0.000000000) *
## 20093) Insurance>=1550 1 0 1 (0.000000000 1.000000000) *
## 10047) NumBedrooms< 6.5 4 0 1 (0.000000000 1.000000000) *
## 157) NumVehicles>=3.5 55 13 0 (0.763636364 0.236363636)
## 314) NumPeople>=6.5 9 0 0 (1.000000000 0.000000000) *
## 315) NumPeople< 6.5 46 13 0 (0.717391304 0.282608696)
## 630) NumRooms< 8.5 16 2 0 (0.875000000 0.125000000)
## 1260) NumBedrooms>=3.5 15 1 0 (0.933333333 0.066666667)
## 2520) ElectricBill< 380 12 0 0 (1.000000000 0.000000000) *
## 2521) ElectricBill>=380 3 1 0 (0.666666667 0.333333333)
## 5042) HouseCosts< 2450 2 0 0 (1.000000000 0.000000000) *
## 5043) HouseCosts>=2450 1 0 1 (0.000000000 1.000000000) *
## 1261) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 631) NumRooms>=8.5 30 11 0 (0.633333333 0.366666667)
## 1262) HouseCosts>=2450 14 3 0 (0.785714286 0.214285714)
## 2524) NumChildren< 1.5 9 1 0 (0.888888889 0.111111111)
## 5048) Insurance>=950 6 0 0 (1.000000000 0.000000000) *
## 5049) Insurance< 950 3 1 0 (0.666666667 0.333333333)
## 10098) Insurance< 850 2 0 0 (1.000000000 0.000000000) *
## 10099) Insurance>=850 1 0 1 (0.000000000 1.000000000) *
## 2525) NumChildren>=1.5 5 2 0 (0.600000000 0.400000000)
## 5050) Insurance< 500 2 0 0 (1.000000000 0.000000000) *
## 5051) Insurance>=500 3 1 1 (0.333333333 0.666666667)
## 10102) Insurance>=1150 1 0 0 (1.000000000 0.000000000) *
## 10103) Insurance< 1150 2 0 1 (0.000000000 1.000000000) *
## 1263) HouseCosts< 2450 16 8 0 (0.500000000 0.500000000)
## 2526) NumWorkers< 2.5 5 1 0 (0.800000000 0.200000000)
## 5052) ElectricBill>=330 4 0 0 (1.000000000 0.000000000) *
## 5053) ElectricBill< 330 1 0 1 (0.000000000 1.000000000) *
## 2527) NumWorkers>=2.5 11 4 1 (0.363636364 0.636363636)
## 5054) Insurance< 1250 8 4 0 (0.500000000 0.500000000)
## 10108) ElectricBill< 435 6 2 0 (0.666666667 0.333333333)
## 20216) NumPeople< 4.5 3 0 0 (1.000000000 0.000000000) *
## 20217) NumPeople>=4.5 3 1 1 (0.333333333 0.666666667)
## 40434) ElectricBill>=335 1 0 0 (1.000000000 0.000000000) *
## 40435) ElectricBill< 335 2 0 1 (0.000000000 1.000000000) *
## 10109) ElectricBill>=435 2 0 1 (0.000000000 1.000000000) *
## 5055) Insurance>=1250 3 0 1 (0.000000000 1.000000000) *
## 79) NumPeople< 3.5 86 22 0 (0.744186047 0.255813953)
## 158) Insurance< 1150 42 6 0 (0.857142857 0.142857143)
## 316) HouseCosts< 2800 29 1 0 (0.965517241 0.034482759)
## 632) ElectricBill>=295 28 0 0 (1.000000000 0.000000000) *
## 633) ElectricBill< 295 1 0 1 (0.000000000 1.000000000) *
## 317) HouseCosts>=2800 13 5 0 (0.615384615 0.384615385)
## 634) NumBedrooms< 4.5 11 3 0 (0.727272727 0.272727273)
## 1268) NumRooms< 9.5 10 2 0 (0.800000000 0.200000000)
## 2536) OwnRent=Mortgage 9 1 0 (0.888888889 0.111111111)
## 5072) ElectricBill>=325 7 0 0 (1.000000000 0.000000000) *
## 5073) ElectricBill< 325 2 1 0 (0.500000000 0.500000000)
## 10146) Insurance< 700 1 0 0 (1.000000000 0.000000000) *
## 10147) Insurance>=700 1 0 1 (0.000000000 1.000000000) *
## 2537) OwnRent=Rented 1 0 1 (0.000000000 1.000000000) *
## 1269) NumRooms>=9.5 1 0 1 (0.000000000 1.000000000) *
## 635) NumBedrooms>=4.5 2 0 1 (0.000000000 1.000000000) *
## 159) Insurance>=1150 44 16 0 (0.636363636 0.363636364)
## 318) NumWorkers< 1.5 8 0 0 (1.000000000 0.000000000) *
## 319) NumWorkers>=1.5 36 16 0 (0.555555556 0.444444444)
## 638) NumChildren>=0.5 8 1 0 (0.875000000 0.125000000)
## 1276) HouseCosts>=2250 7 0 0 (1.000000000 0.000000000) *
## 1277) HouseCosts< 2250 1 0 1 (0.000000000 1.000000000) *
## 639) NumChildren< 0.5 28 13 1 (0.464285714 0.535714286)
## 1278) ElectricBill< 355 14 5 0 (0.642857143 0.357142857)
## 2556) ElectricBill>=345 4 0 0 (1.000000000 0.000000000) *
## 2557) ElectricBill< 345 10 5 0 (0.500000000 0.500000000)
## 5114) HouseCosts>=2400 8 3 0 (0.625000000 0.375000000)
## 10228) NumBedrooms< 6 7 2 0 (0.714285714 0.285714286)
## 20456) NumVehicles< 2.5 4 0 0 (1.000000000 0.000000000) *
## 20457) NumVehicles>=2.5 3 1 1 (0.333333333 0.666666667)
## 40914) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 40915) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 10229) NumBedrooms>=6 1 0 1 (0.000000000 1.000000000) *
## 5115) HouseCosts< 2400 2 0 1 (0.000000000 1.000000000) *
## 1279) ElectricBill>=355 14 4 1 (0.285714286 0.714285714)
## 2558) FoodStamp=Yes 1 0 0 (1.000000000 0.000000000) *
## 2559) FoodStamp=No 13 3 1 (0.230769231 0.769230769)
## 5118) NumWorkers>=2.5 7 3 1 (0.428571429 0.571428571)
## 10236) ElectricBill>=380 5 2 0 (0.600000000 0.400000000)
## 20472) Insurance< 1250 2 0 0 (1.000000000 0.000000000) *
## 20473) Insurance>=1250 3 1 1 (0.333333333 0.666666667)
## 40946) NumRooms>=9.5 1 0 0 (1.000000000 0.000000000) *
## 40947) NumRooms< 9.5 2 0 1 (0.000000000 1.000000000) *
## 10237) ElectricBill< 380 2 0 1 (0.000000000 1.000000000) *
## 5119) NumWorkers< 2.5 6 0 1 (0.000000000 1.000000000) *
## 5) Insurance>=1950 1424 243 0 (0.829353933 0.170646067)
## 10) NumRooms< 6.5 367 17 0 (0.953678474 0.046321526)
## 20) NumVehicles< 3.5 350 14 0 (0.960000000 0.040000000)
## 40) HouseCosts< 3250 338 12 0 (0.964497041 0.035502959)
## 80) NumRooms< 5.5 154 2 0 (0.987012987 0.012987013)
## 160) Insurance< 4350 140 1 0 (0.992857143 0.007142857)
## 320) HouseCosts>=1015 117 0 0 (1.000000000 0.000000000) *
## 321) HouseCosts< 1015 23 1 0 (0.956521739 0.043478261)
## 642) HouseCosts< 985 20 0 0 (1.000000000 0.000000000) *
## 643) HouseCosts>=985 3 1 0 (0.666666667 0.333333333)
## 1286) NumBedrooms>=2.5 2 0 0 (1.000000000 0.000000000) *
## 1287) NumBedrooms< 2.5 1 0 1 (0.000000000 1.000000000) *
## 161) Insurance>=4350 14 1 0 (0.928571429 0.071428571)
## 322) Insurance>=4600 12 0 0 (1.000000000 0.000000000) *
## 323) Insurance< 4600 2 1 0 (0.500000000 0.500000000)
## 646) ElectricBill< 105 1 0 0 (1.000000000 0.000000000) *
## 647) ElectricBill>=105 1 0 1 (0.000000000 1.000000000) *
## 81) NumRooms>=5.5 184 10 0 (0.945652174 0.054347826)
## 162) ElectricBill< 165 84 2 0 (0.976190476 0.023809524)
## 324) NumBedrooms< 3.5 78 1 0 (0.987179487 0.012820513)
## 648) NumChildren< 1.5 60 0 0 (1.000000000 0.000000000) *
## 649) NumChildren>=1.5 18 1 0 (0.944444444 0.055555556)
## 1298) ElectricBill< 140 14 0 0 (1.000000000 0.000000000) *
## 1299) ElectricBill>=140 4 1 0 (0.750000000 0.250000000)
## 2598) Insurance>=2300 2 0 0 (1.000000000 0.000000000) *
## 2599) Insurance< 2300 2 1 0 (0.500000000 0.500000000)
## 5198) Insurance< 2050 1 0 0 (1.000000000 0.000000000) *
## 5199) Insurance>=2050 1 0 1 (0.000000000 1.000000000) *
## 325) NumBedrooms>=3.5 6 1 0 (0.833333333 0.166666667)
## 650) ElectricBill>=110 4 0 0 (1.000000000 0.000000000) *
## 651) ElectricBill< 110 2 1 0 (0.500000000 0.500000000)
## 1302) Insurance< 2750 1 0 0 (1.000000000 0.000000000) *
## 1303) Insurance>=2750 1 0 1 (0.000000000 1.000000000) *
## 163) ElectricBill>=165 100 8 0 (0.920000000 0.080000000)
## 326) NumPeople>=2.5 65 3 0 (0.953846154 0.046153846)
## 652) Insurance>=2150 41 0 0 (1.000000000 0.000000000) *
## 653) Insurance< 2150 24 3 0 (0.875000000 0.125000000)
## 1306) Insurance< 2050 23 2 0 (0.913043478 0.086956522)
## 2612) NumChildren< 1.5 16 0 0 (1.000000000 0.000000000) *
## 2613) NumChildren>=1.5 7 2 0 (0.714285714 0.285714286)
## 5226) NumWorkers>=1.5 4 0 0 (1.000000000 0.000000000) *
## 5227) NumWorkers< 1.5 3 1 1 (0.333333333 0.666666667)
## 10454) NumChildren>=2.5 1 0 0 (1.000000000 0.000000000) *
## 10455) NumChildren< 2.5 2 0 1 (0.000000000 1.000000000) *
## 1307) Insurance>=2050 1 0 1 (0.000000000 1.000000000) *
## 327) NumPeople< 2.5 35 5 0 (0.857142857 0.142857143)
## 654) ElectricBill>=175 34 4 0 (0.882352941 0.117647059)
## 1308) HouseCosts< 1150 13 0 0 (1.000000000 0.000000000) *
## 1309) HouseCosts>=1150 21 4 0 (0.809523810 0.190476190)
## 2618) Insurance< 2350 6 0 0 (1.000000000 0.000000000) *
## 2619) Insurance>=2350 15 4 0 (0.733333333 0.266666667)
## 5238) NumWorkers< 1.5 9 1 0 (0.888888889 0.111111111)
## 10476) Insurance< 5300 8 0 0 (1.000000000 0.000000000) *
## 10477) Insurance>=5300 1 0 1 (0.000000000 1.000000000) *
## 5239) NumWorkers>=1.5 6 3 0 (0.500000000 0.500000000)
## 10478) Insurance>=3650 2 0 0 (1.000000000 0.000000000) *
## 10479) Insurance< 3650 4 1 1 (0.250000000 0.750000000)
## 20958) NumVehicles< 1.5 1 0 0 (1.000000000 0.000000000) *
## 20959) NumVehicles>=1.5 3 0 1 (0.000000000 1.000000000) *
## 655) ElectricBill< 175 1 0 1 (0.000000000 1.000000000) *
## 41) HouseCosts>=3250 12 2 0 (0.833333333 0.166666667)
## 82) ElectricBill>=70 11 1 0 (0.909090909 0.090909091)
## 164) NumBedrooms< 3.5 10 0 0 (1.000000000 0.000000000) *
## 165) NumBedrooms>=3.5 1 0 1 (0.000000000 1.000000000) *
## 83) ElectricBill< 70 1 0 1 (0.000000000 1.000000000) *
## 21) NumVehicles>=3.5 17 3 0 (0.823529412 0.176470588)
## 42) NumRooms>=5.5 13 0 0 (1.000000000 0.000000000) *
## 43) NumRooms< 5.5 4 1 1 (0.250000000 0.750000000)
## 86) HouseCosts>=2800 1 0 0 (1.000000000 0.000000000) *
## 87) HouseCosts< 2800 3 0 1 (0.000000000 1.000000000) *
## 11) NumRooms>=6.5 1057 226 0 (0.786187323 0.213812677)
## 22) Insurance< 3850 878 160 0 (0.817767654 0.182232346)
## 44) NumVehicles< 2.5 555 83 0 (0.850450450 0.149549550)
## 88) NumChildren< 1.5 356 42 0 (0.882022472 0.117977528)
## 176) ElectricBill>=40 354 40 0 (0.887005650 0.112994350)
## 352) ElectricBill< 245 224 16 0 (0.928571429 0.071428571)
## 704) HouseCosts< 3150 209 13 0 (0.937799043 0.062200957)
## 1408) Insurance< 2650 148 6 0 (0.959459459 0.040540541)
## 2816) HouseCosts>=75 145 5 0 (0.965517241 0.034482759)
## 5632) HouseCosts< 2950 139 4 0 (0.971223022 0.028776978)
## 11264) NumChildren< 0.5 115 2 0 (0.982608696 0.017391304)
## 22528) HouseCosts< 2050 92 0 0 (1.000000000 0.000000000) *
## 22529) HouseCosts>=2050 23 2 0 (0.913043478 0.086956522)
## 45058) HouseCosts>=2150 20 0 0 (1.000000000 0.000000000) *
## 45059) HouseCosts< 2150 3 1 1 (0.333333333 0.666666667)
## 90118) Insurance>=2100 1 0 0 (1.000000000 0.000000000) *
## 90119) Insurance< 2100 2 0 1 (0.000000000 1.000000000) *
## 11265) NumChildren>=0.5 24 2 0 (0.916666667 0.083333333)
## 22530) Insurance< 2450 22 1 0 (0.954545455 0.045454545)
## 45060) NumPeople< 3.5 18 0 0 (1.000000000 0.000000000) *
## 45061) NumPeople>=3.5 4 1 0 (0.750000000 0.250000000)
## 90122) HouseCosts>=1250 3 0 0 (1.000000000 0.000000000) *
## 90123) HouseCosts< 1250 1 0 1 (0.000000000 1.000000000) *
## 22531) Insurance>=2450 2 1 0 (0.500000000 0.500000000)
## 45062) ElectricBill>=110 1 0 0 (1.000000000 0.000000000) *
## 45063) ElectricBill< 110 1 0 1 (0.000000000 1.000000000) *
## 5633) HouseCosts>=2950 6 1 0 (0.833333333 0.166666667)
## 11266) ElectricBill>=140 4 0 0 (1.000000000 0.000000000) *
## 11267) ElectricBill< 140 2 1 0 (0.500000000 0.500000000)
## 22534) Insurance< 2250 1 0 0 (1.000000000 0.000000000) *
## 22535) Insurance>=2250 1 0 1 (0.000000000 1.000000000) *
## 2817) HouseCosts< 75 3 1 0 (0.666666667 0.333333333)
## 5634) Insurance< 2150 2 0 0 (1.000000000 0.000000000) *
## 5635) Insurance>=2150 1 0 1 (0.000000000 1.000000000) *
## 1409) Insurance>=2650 61 7 0 (0.885245902 0.114754098)
## 2818) NumVehicles>=0.5 59 6 0 (0.898305085 0.101694915)
## 5636) HouseCosts< 1850 27 1 0 (0.962962963 0.037037037)
## 11272) NumRooms>=7.5 21 0 0 (1.000000000 0.000000000) *
## 11273) NumRooms< 7.5 6 1 0 (0.833333333 0.166666667)
## 22546) ElectricBill>=115 4 0 0 (1.000000000 0.000000000) *
## 22547) ElectricBill< 115 2 1 0 (0.500000000 0.500000000)
## 45094) Insurance>=3350 1 0 0 (1.000000000 0.000000000) *
## 45095) Insurance< 3350 1 0 1 (0.000000000 1.000000000) *
## 5637) HouseCosts>=1850 32 5 0 (0.843750000 0.156250000)
## 11274) HouseCosts>=2250 24 2 0 (0.916666667 0.083333333)
## 22548) Insurance>=2750 22 1 0 (0.954545455 0.045454545)
## 45096) Insurance< 3450 16 0 0 (1.000000000 0.000000000) *
## 45097) Insurance>=3450 6 1 0 (0.833333333 0.166666667)
## 90194) NumRooms>=7.5 5 0 0 (1.000000000 0.000000000) *
## 90195) NumRooms< 7.5 1 0 1 (0.000000000 1.000000000) *
## 22549) Insurance< 2750 2 1 0 (0.500000000 0.500000000)
## 45098) ElectricBill< 185 1 0 0 (1.000000000 0.000000000) *
## 45099) ElectricBill>=185 1 0 1 (0.000000000 1.000000000) *
## 11275) HouseCosts< 2250 8 3 0 (0.625000000 0.375000000)
## 22550) NumRooms>=8.5 3 0 0 (1.000000000 0.000000000) *
## 22551) NumRooms< 8.5 5 2 1 (0.400000000 0.600000000)
## 45102) ElectricBill>=140 3 1 0 (0.666666667 0.333333333)
## 90204) ElectricBill< 175 2 0 0 (1.000000000 0.000000000) *
## 90205) ElectricBill>=175 1 0 1 (0.000000000 1.000000000) *
## 45103) ElectricBill< 140 2 0 1 (0.000000000 1.000000000) *
## 2819) NumVehicles< 0.5 2 1 0 (0.500000000 0.500000000)
## 5638) Insurance< 3200 1 0 0 (1.000000000 0.000000000) *
## 5639) Insurance>=3200 1 0 1 (0.000000000 1.000000000) *
## 705) HouseCosts>=3150 15 3 0 (0.800000000 0.200000000)
## 1410) NumRooms< 10.5 13 1 0 (0.923076923 0.076923077)
## 2820) Insurance< 3050 11 0 0 (1.000000000 0.000000000) *
## 2821) Insurance>=3050 2 1 0 (0.500000000 0.500000000)
## 5642) ElectricBill>=160 1 0 0 (1.000000000 0.000000000) *
## 5643) ElectricBill< 160 1 0 1 (0.000000000 1.000000000) *
## 1411) NumRooms>=10.5 2 0 1 (0.000000000 1.000000000) *
## 353) ElectricBill>=245 130 24 0 (0.815384615 0.184615385)
## 706) HouseCosts>=260 125 21 0 (0.832000000 0.168000000)
## 1412) ElectricBill< 540 122 19 0 (0.844262295 0.155737705)
## 2824) NumVehicles< 1.5 21 0 0 (1.000000000 0.000000000) *
## 2825) NumVehicles>=1.5 101 19 0 (0.811881188 0.188118812)
## 5650) HouseCosts< 1150 14 0 0 (1.000000000 0.000000000) *
## 5651) HouseCosts>=1150 87 19 0 (0.781609195 0.218390805)
## 11302) HouseCosts>=2450 36 4 0 (0.888888889 0.111111111)
## 22604) HouseCosts< 3250 30 2 0 (0.933333333 0.066666667)
## 45208) NumWorkers>=1.5 21 0 0 (1.000000000 0.000000000) *
## 45209) NumWorkers< 1.5 9 2 0 (0.777777778 0.222222222)
## 90418) NumChildren< 0.5 8 1 0 (0.875000000 0.125000000)
## 180836) ElectricBill>=310 4 0 0 (1.000000000 0.000000000) *
## 180837) ElectricBill< 310 4 1 0 (0.750000000 0.250000000)
## 361674) HouseCosts>=2900 3 0 0 (1.000000000 0.000000000) *
## 361675) HouseCosts< 2900 1 0 1 (0.000000000 1.000000000) *
## 90419) NumChildren>=0.5 1 0 1 (0.000000000 1.000000000) *
## 22605) HouseCosts>=3250 6 2 0 (0.666666667 0.333333333)
## 45210) Insurance< 3100 5 1 0 (0.800000000 0.200000000)
## 90420) Insurance>=2150 3 0 0 (1.000000000 0.000000000) *
## 90421) Insurance< 2150 2 1 0 (0.500000000 0.500000000)
## 180842) ElectricBill< 340 1 0 0 (1.000000000 0.000000000) *
## 180843) ElectricBill>=340 1 0 1 (0.000000000 1.000000000) *
## 45211) Insurance>=3100 1 0 1 (0.000000000 1.000000000) *
## 11303) HouseCosts< 2450 51 15 0 (0.705882353 0.294117647)
## 22606) Insurance>=2900 21 3 0 (0.857142857 0.142857143)
## 45212) ElectricBill< 395 18 1 0 (0.944444444 0.055555556)
## 90424) ElectricBill< 345 11 0 0 (1.000000000 0.000000000) *
## 90425) ElectricBill>=345 7 1 0 (0.857142857 0.142857143)
## 180850) NumPeople>=2.5 6 0 0 (1.000000000 0.000000000) *
## 180851) NumPeople< 2.5 1 0 1 (0.000000000 1.000000000) *
## 45213) ElectricBill>=395 3 1 1 (0.333333333 0.666666667)
## 90426) ElectricBill>=475 1 0 0 (1.000000000 0.000000000) *
## 90427) ElectricBill< 475 2 0 1 (0.000000000 1.000000000) *
## 22607) Insurance< 2900 30 12 0 (0.600000000 0.400000000)
## 45214) NumPeople>=4.5 3 0 0 (1.000000000 0.000000000) *
## 45215) NumPeople< 4.5 27 12 0 (0.555555556 0.444444444)
## 90430) HouseCosts< 1950 16 5 0 (0.687500000 0.312500000)
## 180860) NumRooms< 10.5 12 2 0 (0.833333333 0.166666667)
## 361720) ElectricBill>=255 10 1 0 (0.900000000 0.100000000)
## 723440) HouseCosts>=1450 7 0 0 (1.000000000 0.000000000) *
## 723441) HouseCosts< 1450 3 1 0 (0.666666667 0.333333333)
## 1446882) NumBedrooms>=3.5 2 0 0 (1.000000000 0.000000000) *
## 1446883) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 361721) ElectricBill< 255 2 1 0 (0.500000000 0.500000000)
## 723442) Insurance< 2050 1 0 0 (1.000000000 0.000000000) *
## 723443) Insurance>=2050 1 0 1 (0.000000000 1.000000000) *
## 180861) NumRooms>=10.5 4 1 1 (0.250000000 0.750000000)
## 361722) HouseCosts>=1750 1 0 0 (1.000000000 0.000000000) *
## 361723) HouseCosts< 1750 3 0 1 (0.000000000 1.000000000) *
## 90431) HouseCosts>=1950 11 4 1 (0.363636364 0.636363636)
## 180862) NumRooms>=9.5 2 0 0 (1.000000000 0.000000000) *
## 180863) NumRooms< 9.5 9 2 1 (0.222222222 0.777777778)
## 361726) NumRooms< 7.5 3 1 0 (0.666666667 0.333333333)
## 723452) Insurance>=2050 1 0 0 (1.000000000 0.000000000) *
## 723453) Insurance< 2050 2 1 0 (0.500000000 0.500000000)
## 1446906) ElectricBill>=315 1 0 0 (1.000000000 0.000000000) *
## 1446907) ElectricBill< 315 1 0 1 (0.000000000 1.000000000) *
## 361727) NumRooms>=7.5 6 0 1 (0.000000000 1.000000000) *
## 1413) ElectricBill>=540 3 1 1 (0.333333333 0.666666667)
## 2826) Insurance>=2800 1 0 0 (1.000000000 0.000000000) *
## 2827) Insurance< 2800 2 0 1 (0.000000000 1.000000000) *
## 707) HouseCosts< 260 5 2 1 (0.400000000 0.600000000)
## 1414) HouseCosts< 210 3 1 0 (0.666666667 0.333333333)
## 2828) ElectricBill< 350 2 0 0 (1.000000000 0.000000000) *
## 2829) ElectricBill>=350 1 0 1 (0.000000000 1.000000000) *
## 1415) HouseCosts>=210 2 0 1 (0.000000000 1.000000000) *
## 177) ElectricBill< 40 2 0 1 (0.000000000 1.000000000) *
## 89) NumChildren>=1.5 199 41 0 (0.793969849 0.206030151)
## 178) NumRooms< 8.5 101 14 0 (0.861386139 0.138613861)
## 356) Insurance>=2350 47 2 0 (0.957446809 0.042553191)
## 712) ElectricBill< 245 22 0 0 (1.000000000 0.000000000) *
## 713) ElectricBill>=245 25 2 0 (0.920000000 0.080000000)
## 1426) ElectricBill>=255 21 1 0 (0.952380952 0.047619048)
## 2852) Insurance>=2650 15 0 0 (1.000000000 0.000000000) *
## 2853) Insurance< 2650 6 1 0 (0.833333333 0.166666667)
## 5706) NumBedrooms>=3.5 5 0 0 (1.000000000 0.000000000) *
## 5707) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 1427) ElectricBill< 255 4 1 0 (0.750000000 0.250000000)
## 2854) Insurance< 2750 3 0 0 (1.000000000 0.000000000) *
## 2855) Insurance>=2750 1 0 1 (0.000000000 1.000000000) *
## 357) Insurance< 2350 54 12 0 (0.777777778 0.222222222)
## 714) HouseCosts>=1550 44 7 0 (0.840909091 0.159090909)
## 1428) NumBedrooms>=3.5 31 2 0 (0.935483871 0.064516129)
## 2856) NumWorkers>=1.5 24 0 0 (1.000000000 0.000000000) *
## 2857) NumWorkers< 1.5 7 2 0 (0.714285714 0.285714286)
## 5714) HouseCosts>=2650 3 0 0 (1.000000000 0.000000000) *
## 5715) HouseCosts< 2650 4 2 0 (0.500000000 0.500000000)
## 11430) Insurance< 2150 3 1 0 (0.666666667 0.333333333)
## 22860) HouseCosts< 2350 2 0 0 (1.000000000 0.000000000) *
## 22861) HouseCosts>=2350 1 0 1 (0.000000000 1.000000000) *
## 11431) Insurance>=2150 1 0 1 (0.000000000 1.000000000) *
## 1429) NumBedrooms< 3.5 13 5 0 (0.615384615 0.384615385)
## 2858) HouseCosts< 2450 6 1 0 (0.833333333 0.166666667)
## 5716) ElectricBill< 195 3 0 0 (1.000000000 0.000000000) *
## 5717) ElectricBill>=195 3 1 0 (0.666666667 0.333333333)
## 11434) ElectricBill>=220 2 0 0 (1.000000000 0.000000000) *
## 11435) ElectricBill< 220 1 0 1 (0.000000000 1.000000000) *
## 2859) HouseCosts>=2450 7 3 1 (0.428571429 0.571428571)
## 5718) HouseCosts>=2750 5 2 0 (0.600000000 0.400000000)
## 11436) Insurance< 2150 4 1 0 (0.750000000 0.250000000)
## 22872) NumRooms< 7.5 3 0 0 (1.000000000 0.000000000) *
## 22873) NumRooms>=7.5 1 0 1 (0.000000000 1.000000000) *
## 11437) Insurance>=2150 1 0 1 (0.000000000 1.000000000) *
## 5719) HouseCosts< 2750 2 0 1 (0.000000000 1.000000000) *
## 715) HouseCosts< 1550 10 5 0 (0.500000000 0.500000000)
## 1430) ElectricBill>=255 3 0 0 (1.000000000 0.000000000) *
## 1431) ElectricBill< 255 7 2 1 (0.285714286 0.714285714)
## 2862) HouseCosts< 1035 1 0 0 (1.000000000 0.000000000) *
## 2863) HouseCosts>=1035 6 1 1 (0.166666667 0.833333333)
## 5726) ElectricBill< 125 2 1 0 (0.500000000 0.500000000)
## 11452) NumBedrooms>=3.5 1 0 0 (1.000000000 0.000000000) *
## 11453) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 5727) ElectricBill>=125 4 0 1 (0.000000000 1.000000000) *
## 179) NumRooms>=8.5 98 27 0 (0.724489796 0.275510204)
## 358) Insurance>=3150 9 0 0 (1.000000000 0.000000000) *
## 359) Insurance< 3150 89 27 0 (0.696629213 0.303370787)
## 718) NumWorkers< 2.5 87 25 0 (0.712643678 0.287356322)
## 1436) Insurance< 2950 78 20 0 (0.743589744 0.256410256)
## 2872) NumChildren< 4.5 77 19 0 (0.753246753 0.246753247)
## 5744) NumPeople>=5.5 11 0 0 (1.000000000 0.000000000) *
## 5745) NumPeople< 5.5 66 19 0 (0.712121212 0.287878788)
## 11490) NumPeople< 4.5 41 8 0 (0.804878049 0.195121951)
## 22980) ElectricBill>=155 28 3 0 (0.892857143 0.107142857)
## 45960) HouseCosts>=2050 15 0 0 (1.000000000 0.000000000) *
## 45961) HouseCosts< 2050 13 3 0 (0.769230769 0.230769231)
## 91922) HouseCosts< 1500 7 0 0 (1.000000000 0.000000000) *
## 91923) HouseCosts>=1500 6 3 0 (0.500000000 0.500000000)
## 183846) Insurance< 2100 2 0 0 (1.000000000 0.000000000) *
## 183847) Insurance>=2100 4 1 1 (0.250000000 0.750000000)
## 367694) Insurance>=2500 1 0 0 (1.000000000 0.000000000) *
## 367695) Insurance< 2500 3 0 1 (0.000000000 1.000000000) *
## 22981) ElectricBill< 155 13 5 0 (0.615384615 0.384615385)
## 45962) Insurance< 2150 11 3 0 (0.727272727 0.272727273)
## 91924) HouseCosts< 3000 10 2 0 (0.800000000 0.200000000)
## 183848) HouseCosts>=2150 5 0 0 (1.000000000 0.000000000) *
## 183849) HouseCosts< 2150 5 2 0 (0.600000000 0.400000000)
## 367698) HouseCosts< 1600 3 0 0 (1.000000000 0.000000000) *
## 367699) HouseCosts>=1600 2 0 1 (0.000000000 1.000000000) *
## 91925) HouseCosts>=3000 1 0 1 (0.000000000 1.000000000) *
## 45963) Insurance>=2150 2 0 1 (0.000000000 1.000000000) *
## 11491) NumPeople>=4.5 25 11 0 (0.560000000 0.440000000)
## 22982) ElectricBill< 360 20 7 0 (0.650000000 0.350000000)
## 45964) HouseCosts>=2550 8 1 0 (0.875000000 0.125000000)
## 91928) NumRooms< 11 6 0 0 (1.000000000 0.000000000) *
## 91929) NumRooms>=11 2 1 0 (0.500000000 0.500000000)
## 183858) Insurance< 2200 1 0 0 (1.000000000 0.000000000) *
## 183859) Insurance>=2200 1 0 1 (0.000000000 1.000000000) *
## 45965) HouseCosts< 2550 12 6 0 (0.500000000 0.500000000)
## 91930) HouseCosts< 1950 6 1 0 (0.833333333 0.166666667)
## 183860) Insurance< 2300 5 0 0 (1.000000000 0.000000000) *
## 183861) Insurance>=2300 1 0 1 (0.000000000 1.000000000) *
## 91931) HouseCosts>=1950 6 1 1 (0.166666667 0.833333333)
## 183862) NumRooms>=12 1 0 0 (1.000000000 0.000000000) *
## 183863) NumRooms< 12 5 0 1 (0.000000000 1.000000000) *
## 22983) ElectricBill>=360 5 1 1 (0.200000000 0.800000000)
## 45966) Insurance>=2550 1 0 0 (1.000000000 0.000000000) *
## 45967) Insurance< 2550 4 0 1 (0.000000000 1.000000000) *
## 2873) NumChildren>=4.5 1 0 1 (0.000000000 1.000000000) *
## 1437) Insurance>=2950 9 4 1 (0.444444444 0.555555556)
## 2874) ElectricBill< 395 7 3 0 (0.571428571 0.428571429)
## 5748) NumChildren>=2.5 3 0 0 (1.000000000 0.000000000) *
## 5749) NumChildren< 2.5 4 1 1 (0.250000000 0.750000000)
## 11498) ElectricBill>=370 1 0 0 (1.000000000 0.000000000) *
## 11499) ElectricBill< 370 3 0 1 (0.000000000 1.000000000) *
## 2875) ElectricBill>=395 2 0 1 (0.000000000 1.000000000) *
## 719) NumWorkers>=2.5 2 0 1 (0.000000000 1.000000000) *
## 45) NumVehicles>=2.5 323 77 0 (0.761609907 0.238390093)
## 90) NumPeople>=2.5 275 58 0 (0.789090909 0.210909091)
## 180) HouseCosts< 2950 235 43 0 (0.817021277 0.182978723)
## 360) NumBedrooms< 4.5 170 22 0 (0.870588235 0.129411765)
## 720) Insurance< 3700 169 21 0 (0.875739645 0.124260355)
## 1440) ElectricBill< 365 150 16 0 (0.893333333 0.106666667)
## 2880) NumVehicles< 3.5 90 6 0 (0.933333333 0.066666667)
## 5760) ElectricBill< 220 50 1 0 (0.980000000 0.020000000)
## 11520) NumRooms< 10.5 47 0 0 (1.000000000 0.000000000) *
## 11521) NumRooms>=10.5 3 1 0 (0.666666667 0.333333333)
## 23042) Insurance>=2200 2 0 0 (1.000000000 0.000000000) *
## 23043) Insurance< 2200 1 0 1 (0.000000000 1.000000000) *
## 5761) ElectricBill>=220 40 5 0 (0.875000000 0.125000000)
## 11522) HouseCosts>=1050 33 3 0 (0.909090909 0.090909091)
## 23044) ElectricBill>=265 18 0 0 (1.000000000 0.000000000) *
## 23045) ElectricBill< 265 15 3 0 (0.800000000 0.200000000)
## 46090) NumChildren< 2.5 14 2 0 (0.857142857 0.142857143)
## 92180) HouseCosts< 2400 10 0 0 (1.000000000 0.000000000) *
## 92181) HouseCosts>=2400 4 2 0 (0.500000000 0.500000000)
## 184362) Insurance>=2100 3 1 0 (0.666666667 0.333333333)
## 368724) HouseCosts>=2550 2 0 0 (1.000000000 0.000000000) *
## 368725) HouseCosts< 2550 1 0 1 (0.000000000 1.000000000) *
## 184363) Insurance< 2100 1 0 1 (0.000000000 1.000000000) *
## 46091) NumChildren>=2.5 1 0 1 (0.000000000 1.000000000) *
## 11523) HouseCosts< 1050 7 2 0 (0.714285714 0.285714286)
## 23046) HouseCosts< 925 5 0 0 (1.000000000 0.000000000) *
## 23047) HouseCosts>=925 2 0 1 (0.000000000 1.000000000) *
## 2881) NumVehicles>=3.5 60 10 0 (0.833333333 0.166666667)
## 5762) ElectricBill>=145 49 5 0 (0.897959184 0.102040816)
## 11524) ElectricBill< 230 25 1 0 (0.960000000 0.040000000)
## 23048) HouseCosts>=1350 17 0 0 (1.000000000 0.000000000) *
## 23049) HouseCosts< 1350 8 1 0 (0.875000000 0.125000000)
## 46098) NumBedrooms>=3.5 7 0 0 (1.000000000 0.000000000) *
## 46099) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 11525) ElectricBill>=230 24 4 0 (0.833333333 0.166666667)
## 23050) ElectricBill>=245 23 3 0 (0.869565217 0.130434783)
## 46100) NumPeople>=3.5 19 1 0 (0.947368421 0.052631579)
## 92200) ElectricBill>=255 17 0 0 (1.000000000 0.000000000) *
## 92201) ElectricBill< 255 2 1 0 (0.500000000 0.500000000)
## 184402) Insurance< 2650 1 0 0 (1.000000000 0.000000000) *
## 184403) Insurance>=2650 1 0 1 (0.000000000 1.000000000) *
## 46101) NumPeople< 3.5 4 2 0 (0.500000000 0.500000000)
## 92202) Insurance>=2500 3 1 0 (0.666666667 0.333333333)
## 184404) ElectricBill< 285 1 0 0 (1.000000000 0.000000000) *
## 184405) ElectricBill>=285 2 1 0 (0.500000000 0.500000000)
## 368810) ElectricBill>=335 1 0 0 (1.000000000 0.000000000) *
## 368811) ElectricBill< 335 1 0 1 (0.000000000 1.000000000) *
## 92203) Insurance< 2500 1 0 1 (0.000000000 1.000000000) *
## 23051) ElectricBill< 245 1 0 1 (0.000000000 1.000000000) *
## 5763) ElectricBill< 145 11 5 0 (0.545454545 0.454545455)
## 11526) Insurance>=2700 3 0 0 (1.000000000 0.000000000) *
## 11527) Insurance< 2700 8 3 1 (0.375000000 0.625000000)
## 23054) NumRooms< 7.5 2 0 0 (1.000000000 0.000000000) *
## 23055) NumRooms>=7.5 6 1 1 (0.166666667 0.833333333)
## 46110) ElectricBill< 110 2 1 0 (0.500000000 0.500000000)
## 92220) HouseCosts>=805 1 0 0 (1.000000000 0.000000000) *
## 92221) HouseCosts< 805 1 0 1 (0.000000000 1.000000000) *
## 46111) ElectricBill>=110 4 0 1 (0.000000000 1.000000000) *
## 1441) ElectricBill>=365 19 5 0 (0.736842105 0.263157895)
## 2882) NumPeople>=4.5 8 0 0 (1.000000000 0.000000000) *
## 2883) NumPeople< 4.5 11 5 0 (0.545454545 0.454545455)
## 5766) NumBedrooms< 3.5 4 0 0 (1.000000000 0.000000000) *
## 5767) NumBedrooms>=3.5 7 2 1 (0.285714286 0.714285714)
## 11534) HouseCosts< 725 1 0 0 (1.000000000 0.000000000) *
## 11535) HouseCosts>=725 6 1 1 (0.166666667 0.833333333)
## 23070) HouseCosts>=2500 1 0 0 (1.000000000 0.000000000) *
## 23071) HouseCosts< 2500 5 0 1 (0.000000000 1.000000000) *
## 721) Insurance>=3700 1 0 1 (0.000000000 1.000000000) *
## 361) NumBedrooms>=4.5 65 21 0 (0.676923077 0.323076923)
## 722) Insurance< 2450 34 6 0 (0.823529412 0.176470588)
## 1444) HouseCosts>=815 30 3 0 (0.900000000 0.100000000)
## 2888) ElectricBill>=110 29 2 0 (0.931034483 0.068965517)
## 5776) HouseCosts< 2750 28 1 0 (0.964285714 0.035714286)
## 11552) HouseCosts>=1550 23 0 0 (1.000000000 0.000000000) *
## 11553) HouseCosts< 1550 5 1 0 (0.800000000 0.200000000)
## 23106) Insurance< 2150 3 0 0 (1.000000000 0.000000000) *
## 23107) Insurance>=2150 2 1 0 (0.500000000 0.500000000)
## 46214) Insurance>=2250 1 0 0 (1.000000000 0.000000000) *
## 46215) Insurance< 2250 1 0 1 (0.000000000 1.000000000) *
## 5777) HouseCosts>=2750 1 0 1 (0.000000000 1.000000000) *
## 2889) ElectricBill< 110 1 0 1 (0.000000000 1.000000000) *
## 1445) HouseCosts< 815 4 1 1 (0.250000000 0.750000000)
## 2890) Insurance>=2150 1 0 0 (1.000000000 0.000000000) *
## 2891) Insurance< 2150 3 0 1 (0.000000000 1.000000000) *
## 723) Insurance>=2450 31 15 0 (0.516129032 0.483870968)
## 1446) HouseCosts< 1450 12 2 0 (0.833333333 0.166666667)
## 2892) ElectricBill>=170 11 1 0 (0.909090909 0.090909091)
## 5784) HouseCosts>=445 9 0 0 (1.000000000 0.000000000) *
## 5785) HouseCosts< 445 2 1 0 (0.500000000 0.500000000)
## 11570) Insurance< 2750 1 0 0 (1.000000000 0.000000000) *
## 11571) Insurance>=2750 1 0 1 (0.000000000 1.000000000) *
## 2893) ElectricBill< 170 1 0 1 (0.000000000 1.000000000) *
## 1447) HouseCosts>=1450 19 6 1 (0.315789474 0.684210526)
## 2894) NumPeople>=4.5 11 5 0 (0.545454545 0.454545455)
## 5788) NumVehicles< 4.5 8 2 0 (0.750000000 0.250000000)
## 11576) Insurance>=2700 5 0 0 (1.000000000 0.000000000) *
## 11577) Insurance< 2700 3 1 1 (0.333333333 0.666666667)
## 23154) Insurance< 2550 1 0 0 (1.000000000 0.000000000) *
## 23155) Insurance>=2550 2 0 1 (0.000000000 1.000000000) *
## 5789) NumVehicles>=4.5 3 0 1 (0.000000000 1.000000000) *
## 2895) NumPeople< 4.5 8 0 1 (0.000000000 1.000000000) *
## 181) HouseCosts>=2950 40 15 0 (0.625000000 0.375000000)
## 362) HouseCosts>=3250 10 1 0 (0.900000000 0.100000000)
## 724) ElectricBill< 360 8 0 0 (1.000000000 0.000000000) *
## 725) ElectricBill>=360 2 1 0 (0.500000000 0.500000000)
## 1450) Insurance>=2300 1 0 0 (1.000000000 0.000000000) *
## 1451) Insurance< 2300 1 0 1 (0.000000000 1.000000000) *
## 363) HouseCosts< 3250 30 14 0 (0.533333333 0.466666667)
## 726) NumBedrooms>=6.5 4 0 0 (1.000000000 0.000000000) *
## 727) NumBedrooms< 6.5 26 12 1 (0.461538462 0.538461538)
## 1454) HouseCosts< 3050 19 8 0 (0.578947368 0.421052632)
## 2908) NumChildren< 0.5 7 1 0 (0.857142857 0.142857143)
## 5816) NumWorkers>=1.5 6 0 0 (1.000000000 0.000000000) *
## 5817) NumWorkers< 1.5 1 0 1 (0.000000000 1.000000000) *
## 2909) NumChildren>=0.5 12 5 1 (0.416666667 0.583333333)
## 5818) ElectricBill< 125 2 0 0 (1.000000000 0.000000000) *
## 5819) ElectricBill>=125 10 3 1 (0.300000000 0.700000000)
## 11638) ElectricBill>=295 5 2 0 (0.600000000 0.400000000)
## 23276) Insurance< 2750 3 0 0 (1.000000000 0.000000000) *
## 23277) Insurance>=2750 2 0 1 (0.000000000 1.000000000) *
## 11639) ElectricBill< 295 5 0 1 (0.000000000 1.000000000) *
## 1455) HouseCosts>=3050 7 1 1 (0.142857143 0.857142857)
## 2910) ElectricBill< 175 1 0 0 (1.000000000 0.000000000) *
## 2911) ElectricBill>=175 6 0 1 (0.000000000 1.000000000) *
## 91) NumPeople< 2.5 48 19 0 (0.604166667 0.395833333)
## 182) NumVehicles>=3.5 8 0 0 (1.000000000 0.000000000) *
## 183) NumVehicles< 3.5 40 19 0 (0.525000000 0.475000000)
## 366) NumBedrooms< 6.5 37 16 0 (0.567567568 0.432432432)
## 732) NumRooms>=7.5 27 9 0 (0.666666667 0.333333333)
## 1464) NumRooms< 8.5 14 2 0 (0.857142857 0.142857143)
## 2928) ElectricBill>=46 13 1 0 (0.923076923 0.076923077)
## 5856) ElectricBill< 280 10 0 0 (1.000000000 0.000000000) *
## 5857) ElectricBill>=280 3 1 0 (0.666666667 0.333333333)
## 11714) ElectricBill>=325 2 0 0 (1.000000000 0.000000000) *
## 11715) ElectricBill< 325 1 0 1 (0.000000000 1.000000000) *
## 2929) ElectricBill< 46 1 0 1 (0.000000000 1.000000000) *
## 1465) NumRooms>=8.5 13 6 1 (0.461538462 0.538461538)
## 2930) NumBedrooms>=4.5 5 1 0 (0.800000000 0.200000000)
## 5860) Insurance>=2050 4 0 0 (1.000000000 0.000000000) *
## 5861) Insurance< 2050 1 0 1 (0.000000000 1.000000000) *
## 2931) NumBedrooms< 4.5 8 2 1 (0.250000000 0.750000000)
## 5862) Insurance< 2100 1 0 0 (1.000000000 0.000000000) *
## 5863) Insurance>=2100 7 1 1 (0.142857143 0.857142857)
## 11726) Insurance>=3250 2 1 0 (0.500000000 0.500000000)
## 23452) ElectricBill>=135 1 0 0 (1.000000000 0.000000000) *
## 23453) ElectricBill< 135 1 0 1 (0.000000000 1.000000000) *
## 11727) Insurance< 3250 5 0 1 (0.000000000 1.000000000) *
## 733) NumRooms< 7.5 10 3 1 (0.300000000 0.700000000)
## 1466) Insurance< 2450 5 2 0 (0.600000000 0.400000000)
## 2932) NumBedrooms< 3.5 3 0 0 (1.000000000 0.000000000) *
## 2933) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 1467) Insurance>=2450 5 0 1 (0.000000000 1.000000000) *
## 367) NumBedrooms>=6.5 3 0 1 (0.000000000 1.000000000) *
## 23) Insurance>=3850 179 66 0 (0.631284916 0.368715084)
## 46) HouseCosts>=350 173 60 0 (0.653179191 0.346820809)
## 92) NumRooms< 8.5 84 23 0 (0.726190476 0.273809524)
## 184) NumBedrooms< 6.5 82 21 0 (0.743902439 0.256097561)
## 368) Insurance< 4250 18 1 0 (0.944444444 0.055555556)
## 736) ElectricBill< 340 15 0 0 (1.000000000 0.000000000) *
## 737) ElectricBill>=340 3 1 0 (0.666666667 0.333333333)
## 1474) ElectricBill>=425 2 0 0 (1.000000000 0.000000000) *
## 1475) ElectricBill< 425 1 0 1 (0.000000000 1.000000000) *
## 369) Insurance>=4250 64 20 0 (0.687500000 0.312500000)
## 738) NumWorkers>=1.5 36 8 0 (0.777777778 0.222222222)
## 1476) ElectricBill< 425 32 5 0 (0.843750000 0.156250000)
## 2952) HouseCosts>=850 29 3 0 (0.896551724 0.103448276)
## 5904) Insurance>=4350 27 2 0 (0.925925926 0.074074074)
## 11808) NumBedrooms< 4.5 25 1 0 (0.960000000 0.040000000)
## 23616) NumVehicles>=1.5 20 0 0 (1.000000000 0.000000000) *
## 23617) NumVehicles< 1.5 5 1 0 (0.800000000 0.200000000)
## 47234) Insurance>=5800 4 0 0 (1.000000000 0.000000000) *
## 47235) Insurance< 5800 1 0 1 (0.000000000 1.000000000) *
## 11809) NumBedrooms>=4.5 2 1 0 (0.500000000 0.500000000)
## 23618) ElectricBill>=275 1 0 0 (1.000000000 0.000000000) *
## 23619) ElectricBill< 275 1 0 1 (0.000000000 1.000000000) *
## 5905) Insurance< 4350 2 1 0 (0.500000000 0.500000000)
## 11810) ElectricBill< 305 1 0 0 (1.000000000 0.000000000) *
## 11811) ElectricBill>=305 1 0 1 (0.000000000 1.000000000) *
## 2953) HouseCosts< 850 3 1 1 (0.333333333 0.666666667)
## 5906) Insurance>=5550 2 1 0 (0.500000000 0.500000000)
## 11812) ElectricBill< 240 1 0 0 (1.000000000 0.000000000) *
## 11813) ElectricBill>=240 1 0 1 (0.000000000 1.000000000) *
## 5907) Insurance< 5550 1 0 1 (0.000000000 1.000000000) *
## 1477) ElectricBill>=425 4 1 1 (0.250000000 0.750000000)
## 2954) HouseCosts>=2500 1 0 0 (1.000000000 0.000000000) *
## 2955) HouseCosts< 2500 3 0 1 (0.000000000 1.000000000) *
## 739) NumWorkers< 1.5 28 12 0 (0.571428571 0.428571429)
## 1478) ElectricBill>=485 4 0 0 (1.000000000 0.000000000) *
## 1479) ElectricBill< 485 24 12 0 (0.500000000 0.500000000)
## 2958) HouseCosts< 2700 18 7 0 (0.611111111 0.388888889)
## 5916) HouseCosts>=1750 5 0 0 (1.000000000 0.000000000) *
## 5917) HouseCosts< 1750 13 6 1 (0.461538462 0.538461538)
## 11834) HouseCosts< 1350 7 2 0 (0.714285714 0.285714286)
## 23668) NumChildren< 1 6 1 0 (0.833333333 0.166666667)
## 47336) ElectricBill>=280 3 0 0 (1.000000000 0.000000000) *
## 47337) ElectricBill< 280 3 1 0 (0.666666667 0.333333333)
## 94674) ElectricBill< 235 2 0 0 (1.000000000 0.000000000) *
## 94675) ElectricBill>=235 1 0 1 (0.000000000 1.000000000) *
## 23669) NumChildren>=1 1 0 1 (0.000000000 1.000000000) *
## 11835) HouseCosts>=1350 6 1 1 (0.166666667 0.833333333)
## 23670) ElectricBill>=295 2 1 0 (0.500000000 0.500000000)
## 47340) ElectricBill< 360 1 0 0 (1.000000000 0.000000000) *
## 47341) ElectricBill>=360 1 0 1 (0.000000000 1.000000000) *
## 23671) ElectricBill< 295 4 0 1 (0.000000000 1.000000000) *
## 2959) HouseCosts>=2700 6 1 1 (0.166666667 0.833333333)
## 5918) HouseCosts< 3100 3 1 1 (0.333333333 0.666666667)
## 11836) ElectricBill>=195 1 0 0 (1.000000000 0.000000000) *
## 11837) ElectricBill< 195 2 0 1 (0.000000000 1.000000000) *
## 5919) HouseCosts>=3100 3 0 1 (0.000000000 1.000000000) *
## 185) NumBedrooms>=6.5 2 0 1 (0.000000000 1.000000000) *
## 93) NumRooms>=8.5 89 37 0 (0.584269663 0.415730337)
## 186) NumBedrooms>=6.5 18 4 0 (0.777777778 0.222222222)
## 372) HouseCosts< 3150 15 2 0 (0.866666667 0.133333333)
## 744) NumRooms< 17 7 0 0 (1.000000000 0.000000000) *
## 745) NumRooms>=17 8 2 0 (0.750000000 0.250000000)
## 1490) NumWorkers< 2.5 7 1 0 (0.857142857 0.142857143)
## 2980) NumChildren>=0.5 5 0 0 (1.000000000 0.000000000) *
## 2981) NumChildren< 0.5 2 1 0 (0.500000000 0.500000000)
## 5962) Insurance< 5300 1 0 0 (1.000000000 0.000000000) *
## 5963) Insurance>=5300 1 0 1 (0.000000000 1.000000000) *
## 1491) NumWorkers>=2.5 1 0 1 (0.000000000 1.000000000) *
## 373) HouseCosts>=3150 3 1 1 (0.333333333 0.666666667)
## 746) Insurance< 4250 1 0 0 (1.000000000 0.000000000) *
## 747) Insurance>=4250 2 0 1 (0.000000000 1.000000000) *
## 187) NumBedrooms< 6.5 71 33 0 (0.535211268 0.464788732)
## 374) NumPeople>=7.5 2 0 0 (1.000000000 0.000000000) *
## 375) NumPeople< 7.5 69 33 0 (0.521739130 0.478260870)
## 750) NumChildren< 1.5 52 22 0 (0.576923077 0.423076923)
## 1500) HouseCosts< 1950 21 6 0 (0.714285714 0.285714286)
## 3000) HouseCosts>=955 12 1 0 (0.916666667 0.083333333)
## 6000) ElectricBill< 405 10 0 0 (1.000000000 0.000000000) *
## 6001) ElectricBill>=405 2 1 0 (0.500000000 0.500000000)
## 12002) Insurance< 5300 1 0 0 (1.000000000 0.000000000) *
## 12003) Insurance>=5300 1 0 1 (0.000000000 1.000000000) *
## 3001) HouseCosts< 955 9 4 1 (0.444444444 0.555555556)
## 6002) HouseCosts< 725 5 1 0 (0.800000000 0.200000000)
## 12004) Insurance>=4450 4 0 0 (1.000000000 0.000000000) *
## 12005) Insurance< 4450 1 0 1 (0.000000000 1.000000000) *
## 6003) HouseCosts>=725 4 0 1 (0.000000000 1.000000000) *
## 1501) HouseCosts>=1950 31 15 1 (0.483870968 0.516129032)
## 3002) NumPeople>=2.5 16 5 0 (0.687500000 0.312500000)
## 6004) ElectricBill< 305 9 1 0 (0.888888889 0.111111111)
## 12008) ElectricBill>=155 8 0 0 (1.000000000 0.000000000) *
## 12009) ElectricBill< 155 1 0 1 (0.000000000 1.000000000) *
## 6005) ElectricBill>=305 7 3 1 (0.428571429 0.571428571)
## 12010) NumPeople>=3.5 4 1 0 (0.750000000 0.250000000)
## 24020) HouseCosts>=2150 3 0 0 (1.000000000 0.000000000) *
## 24021) HouseCosts< 2150 1 0 1 (0.000000000 1.000000000) *
## 12011) NumPeople< 3.5 3 0 1 (0.000000000 1.000000000) *
## 3003) NumPeople< 2.5 15 4 1 (0.266666667 0.733333333)
## 6006) ElectricBill>=355 5 2 0 (0.600000000 0.400000000)
## 12012) ElectricBill< 380 2 0 0 (1.000000000 0.000000000) *
## 12013) ElectricBill>=380 3 1 1 (0.333333333 0.666666667)
## 24026) ElectricBill>=430 1 0 0 (1.000000000 0.000000000) *
## 24027) ElectricBill< 430 2 0 1 (0.000000000 1.000000000) *
## 6007) ElectricBill< 355 10 1 1 (0.100000000 0.900000000)
## 12014) HouseCosts>=2950 1 0 0 (1.000000000 0.000000000) *
## 12015) HouseCosts< 2950 9 0 1 (0.000000000 1.000000000) *
## 751) NumChildren>=1.5 17 6 1 (0.352941176 0.647058824)
## 1502) ElectricBill>=275 8 3 0 (0.625000000 0.375000000)
## 3004) NumVehicles< 2.5 5 0 0 (1.000000000 0.000000000) *
## 3005) NumVehicles>=2.5 3 0 1 (0.000000000 1.000000000) *
## 1503) ElectricBill< 275 9 1 1 (0.111111111 0.888888889)
## 3006) NumRooms>=10.5 3 1 1 (0.333333333 0.666666667)
## 6012) HouseCosts< 1900 1 0 0 (1.000000000 0.000000000) *
## 6013) HouseCosts>=1900 2 0 1 (0.000000000 1.000000000) *
## 3007) NumRooms< 10.5 6 0 1 (0.000000000 1.000000000) *
## 47) HouseCosts< 350 6 0 1 (0.000000000 1.000000000) *
## 3) HouseCosts>=3440 978 394 0 (0.597137014 0.402862986)
## 6) HouseCosts< 4450 575 167 0 (0.709565217 0.290434783)
## 12) Insurance< 1850 337 72 0 (0.786350148 0.213649852)
## 24) HouseCosts< 4150 287 51 0 (0.822299652 0.177700348)
## 48) NumPeople>=4.5 79 6 0 (0.924050633 0.075949367)
## 96) NumRooms>=4.5 78 5 0 (0.935897436 0.064102564)
## 192) NumRooms< 10.5 69 3 0 (0.956521739 0.043478261)
## 384) ElectricBill< 475 64 2 0 (0.968750000 0.031250000)
## 768) ElectricBill>=105 57 1 0 (0.982456140 0.017543860)
## 1536) HouseCosts>=3550 44 0 0 (1.000000000 0.000000000) *
## 1537) HouseCosts< 3550 13 1 0 (0.923076923 0.076923077)
## 3074) Insurance>=1150 9 0 0 (1.000000000 0.000000000) *
## 3075) Insurance< 1150 4 1 0 (0.750000000 0.250000000)
## 6150) Insurance< 1000 3 0 0 (1.000000000 0.000000000) *
## 6151) Insurance>=1000 1 0 1 (0.000000000 1.000000000) *
## 769) ElectricBill< 105 7 1 0 (0.857142857 0.142857143)
## 1538) Insurance>=750 5 0 0 (1.000000000 0.000000000) *
## 1539) Insurance< 750 2 1 0 (0.500000000 0.500000000)
## 3078) Insurance< 250 1 0 0 (1.000000000 0.000000000) *
## 3079) Insurance>=250 1 0 1 (0.000000000 1.000000000) *
## 385) ElectricBill>=475 5 1 0 (0.800000000 0.200000000)
## 770) NumChildren< 2.5 4 0 0 (1.000000000 0.000000000) *
## 771) NumChildren>=2.5 1 0 1 (0.000000000 1.000000000) *
## 193) NumRooms>=10.5 9 2 0 (0.777777778 0.222222222)
## 386) Insurance< 1300 5 0 0 (1.000000000 0.000000000) *
## 387) Insurance>=1300 4 2 0 (0.500000000 0.500000000)
## 774) HouseCosts>=3750 2 0 0 (1.000000000 0.000000000) *
## 775) HouseCosts< 3750 2 0 1 (0.000000000 1.000000000) *
## 97) NumRooms< 4.5 1 0 1 (0.000000000 1.000000000) *
## 49) NumPeople< 4.5 208 45 0 (0.783653846 0.216346154)
## 98) OwnRent=Mortgage 194 38 0 (0.804123711 0.195876289)
## 196) NumRooms< 7.5 102 13 0 (0.872549020 0.127450980)
## 392) ElectricBill>=25.5 101 12 0 (0.881188119 0.118811881)
## 784) HouseCosts>=3490 100 11 0 (0.890000000 0.110000000)
## 1568) ElectricBill< 290 73 4 0 (0.945205479 0.054794521)
## 3136) NumVehicles< 3.5 71 3 0 (0.957746479 0.042253521)
## 6272) NumPeople>=2.5 51 1 0 (0.980392157 0.019607843)
## 12544) NumWorkers>=1.5 40 0 0 (1.000000000 0.000000000) *
## 12545) NumWorkers< 1.5 11 1 0 (0.909090909 0.090909091)
## 25090) HouseCosts< 3850 10 0 0 (1.000000000 0.000000000) *
## 25091) HouseCosts>=3850 1 0 1 (0.000000000 1.000000000) *
## 6273) NumPeople< 2.5 20 2 0 (0.900000000 0.100000000)
## 12546) HouseCosts>=3540 10 0 0 (1.000000000 0.000000000) *
## 12547) HouseCosts< 3540 10 2 0 (0.800000000 0.200000000)
## 25094) ElectricBill< 115 4 0 0 (1.000000000 0.000000000) *
## 25095) ElectricBill>=115 6 2 0 (0.666666667 0.333333333)
## 50190) Insurance>=1550 3 0 0 (1.000000000 0.000000000) *
## 50191) Insurance< 1550 3 1 1 (0.333333333 0.666666667)
## 100382) Insurance< 285 1 0 0 (1.000000000 0.000000000) *
## 100383) Insurance>=285 2 0 1 (0.000000000 1.000000000) *
## 3137) NumVehicles>=3.5 2 1 0 (0.500000000 0.500000000)
## 6274) Insurance>=1300 1 0 0 (1.000000000 0.000000000) *
## 6275) Insurance< 1300 1 0 1 (0.000000000 1.000000000) *
## 1569) ElectricBill>=290 27 7 0 (0.740740741 0.259259259)
## 3138) Insurance< 1450 18 2 0 (0.888888889 0.111111111)
## 6276) Insurance>=850 10 0 0 (1.000000000 0.000000000) *
## 6277) Insurance< 850 8 2 0 (0.750000000 0.250000000)
## 12554) Insurance< 690 7 1 0 (0.857142857 0.142857143)
## 25108) NumChildren>=0.5 5 0 0 (1.000000000 0.000000000) *
## 25109) NumChildren< 0.5 2 1 0 (0.500000000 0.500000000)
## 50218) Insurance>=340 1 0 0 (1.000000000 0.000000000) *
## 50219) Insurance< 340 1 0 1 (0.000000000 1.000000000) *
## 12555) Insurance>=690 1 0 1 (0.000000000 1.000000000) *
## 3139) Insurance>=1450 9 4 1 (0.444444444 0.555555556)
## 6278) NumChildren>=0.5 5 1 0 (0.800000000 0.200000000)
## 12556) HouseCosts< 3900 3 0 0 (1.000000000 0.000000000) *
## 12557) HouseCosts>=3900 2 1 0 (0.500000000 0.500000000)
## 25114) Insurance>=1550 1 0 0 (1.000000000 0.000000000) *
## 25115) Insurance< 1550 1 0 1 (0.000000000 1.000000000) *
## 6279) NumChildren< 0.5 4 0 1 (0.000000000 1.000000000) *
## 785) HouseCosts< 3490 1 0 1 (0.000000000 1.000000000) *
## 393) ElectricBill< 25.5 1 0 1 (0.000000000 1.000000000) *
## 197) NumRooms>=7.5 92 25 0 (0.728260870 0.271739130)
## 394) HouseCosts>=3550 64 11 0 (0.828125000 0.171875000)
## 788) HouseCosts< 3750 22 1 0 (0.954545455 0.045454545)
## 1576) ElectricBill>=115 17 0 0 (1.000000000 0.000000000) *
## 1577) ElectricBill< 115 5 1 0 (0.800000000 0.200000000)
## 3154) NumBedrooms>=3.5 4 0 0 (1.000000000 0.000000000) *
## 3155) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 789) HouseCosts>=3750 42 10 0 (0.761904762 0.238095238)
## 1578) NumWorkers< 2.5 37 7 0 (0.810810811 0.189189189)
## 3156) ElectricBill>=120 34 5 0 (0.852941176 0.147058824)
## 6312) ElectricBill< 195 12 0 0 (1.000000000 0.000000000) *
## 6313) ElectricBill>=195 22 5 0 (0.772727273 0.227272727)
## 12626) Insurance< 1750 19 3 0 (0.842105263 0.157894737)
## 25252) Insurance>=350 18 2 0 (0.888888889 0.111111111)
## 50504) HouseCosts>=3850 10 0 0 (1.000000000 0.000000000) *
## 50505) HouseCosts< 3850 8 2 0 (0.750000000 0.250000000)
## 101010) Insurance>=1250 5 0 0 (1.000000000 0.000000000) *
## 101011) Insurance< 1250 3 1 1 (0.333333333 0.666666667)
## 202022) ElectricBill>=420 1 0 0 (1.000000000 0.000000000) *
## 202023) ElectricBill< 420 2 0 1 (0.000000000 1.000000000) *
## 25253) Insurance< 350 1 0 1 (0.000000000 1.000000000) *
## 12627) Insurance>=1750 3 1 1 (0.333333333 0.666666667)
## 25254) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 25255) NumBedrooms>=3.5 2 0 1 (0.000000000 1.000000000) *
## 3157) ElectricBill< 120 3 1 1 (0.333333333 0.666666667)
## 6314) Insurance>=1650 1 0 0 (1.000000000 0.000000000) *
## 6315) Insurance< 1650 2 0 1 (0.000000000 1.000000000) *
## 1579) NumWorkers>=2.5 5 2 1 (0.400000000 0.600000000)
## 3158) ElectricBill>=235 3 1 0 (0.666666667 0.333333333)
## 6316) Insurance>=1300 1 0 0 (1.000000000 0.000000000) *
## 6317) Insurance< 1300 2 1 0 (0.500000000 0.500000000)
## 12634) ElectricBill< 290 1 0 0 (1.000000000 0.000000000) *
## 12635) ElectricBill>=290 1 0 1 (0.000000000 1.000000000) *
## 3159) ElectricBill< 235 2 0 1 (0.000000000 1.000000000) *
## 395) HouseCosts< 3550 28 14 0 (0.500000000 0.500000000)
## 790) NumWorkers< 1.5 7 2 0 (0.714285714 0.285714286)
## 1580) ElectricBill>=250 4 0 0 (1.000000000 0.000000000) *
## 1581) ElectricBill< 250 3 1 1 (0.333333333 0.666666667)
## 3162) ElectricBill< 195 1 0 0 (1.000000000 0.000000000) *
## 3163) ElectricBill>=195 2 0 1 (0.000000000 1.000000000) *
## 791) NumWorkers>=1.5 21 9 1 (0.428571429 0.571428571)
## 1582) Insurance>=1250 10 3 0 (0.700000000 0.300000000)
## 3164) NumRooms>=9 5 0 0 (1.000000000 0.000000000) *
## 3165) NumRooms< 9 5 2 1 (0.400000000 0.600000000)
## 6330) ElectricBill< 160 1 0 0 (1.000000000 0.000000000) *
## 6331) ElectricBill>=160 4 1 1 (0.250000000 0.750000000)
## 12662) ElectricBill>=335 1 0 0 (1.000000000 0.000000000) *
## 12663) ElectricBill< 335 3 0 1 (0.000000000 1.000000000) *
## 1583) Insurance< 1250 11 2 1 (0.181818182 0.818181818)
## 3166) NumVehicles< 0.5 1 0 0 (1.000000000 0.000000000) *
## 3167) NumVehicles>=0.5 10 1 1 (0.100000000 0.900000000)
## 6334) NumVehicles>=3.5 3 1 1 (0.333333333 0.666666667)
## 12668) ElectricBill< 185 1 0 0 (1.000000000 0.000000000) *
## 12669) ElectricBill>=185 2 0 1 (0.000000000 1.000000000) *
## 6335) NumVehicles< 3.5 7 0 1 (0.000000000 1.000000000) *
## 99) OwnRent=Rented 14 7 0 (0.500000000 0.500000000)
## 198) NumChildren< 1.5 10 3 0 (0.700000000 0.300000000)
## 396) ElectricBill< 410 8 1 0 (0.875000000 0.125000000)
## 792) NumPeople>=2.5 6 0 0 (1.000000000 0.000000000) *
## 793) NumPeople< 2.5 2 1 0 (0.500000000 0.500000000)
## 1586) ElectricBill>=250 1 0 0 (1.000000000 0.000000000) *
## 1587) ElectricBill< 250 1 0 1 (0.000000000 1.000000000) *
## 397) ElectricBill>=410 2 0 1 (0.000000000 1.000000000) *
## 199) NumChildren>=1.5 4 0 1 (0.000000000 1.000000000) *
## 25) HouseCosts>=4150 50 21 0 (0.580000000 0.420000000)
## 50) ElectricBill< 335 38 11 0 (0.710526316 0.289473684)
## 100) Insurance< 1650 35 8 0 (0.771428571 0.228571429)
## 200) NumRooms< 10.5 31 5 0 (0.838709677 0.161290323)
## 400) Insurance< 1250 15 1 0 (0.933333333 0.066666667)
## 800) NumChildren< 2.5 12 0 0 (1.000000000 0.000000000) *
## 801) NumChildren>=2.5 3 1 0 (0.666666667 0.333333333)
## 1602) NumBedrooms>=3.5 2 0 0 (1.000000000 0.000000000) *
## 1603) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 401) Insurance>=1250 16 4 0 (0.750000000 0.250000000)
## 802) NumRooms< 7.5 7 0 0 (1.000000000 0.000000000) *
## 803) NumRooms>=7.5 9 4 0 (0.555555556 0.444444444)
## 1606) NumBedrooms>=4.5 3 0 0 (1.000000000 0.000000000) *
## 1607) NumBedrooms< 4.5 6 2 1 (0.333333333 0.666666667)
## 3214) NumChildren< 0.5 3 1 0 (0.666666667 0.333333333)
## 6428) ElectricBill>=140 2 0 0 (1.000000000 0.000000000) *
## 6429) ElectricBill< 140 1 0 1 (0.000000000 1.000000000) *
## 3215) NumChildren>=0.5 3 0 1 (0.000000000 1.000000000) *
## 201) NumRooms>=10.5 4 1 1 (0.250000000 0.750000000)
## 402) NumBedrooms>=6.5 1 0 0 (1.000000000 0.000000000) *
## 403) NumBedrooms< 6.5 3 0 1 (0.000000000 1.000000000) *
## 101) Insurance>=1650 3 0 1 (0.000000000 1.000000000) *
## 51) ElectricBill>=335 12 2 1 (0.166666667 0.833333333)
## 102) Insurance< 650 2 1 0 (0.500000000 0.500000000)
## 204) Insurance>=530 1 0 0 (1.000000000 0.000000000) *
## 205) Insurance< 530 1 0 1 (0.000000000 1.000000000) *
## 103) Insurance>=650 10 1 1 (0.100000000 0.900000000)
## 206) NumRooms>=12.5 1 0 0 (1.000000000 0.000000000) *
## 207) NumRooms< 12.5 9 0 1 (0.000000000 1.000000000) *
## 13) Insurance>=1850 238 95 0 (0.600840336 0.399159664)
## 26) NumBedrooms< 3.5 54 11 0 (0.796296296 0.203703704)
## 52) NumRooms>=5.5 46 6 0 (0.869565217 0.130434783)
## 104) Insurance>=1950 45 5 0 (0.888888889 0.111111111)
## 208) Insurance< 2900 27 0 0 (1.000000000 0.000000000) *
## 209) Insurance>=2900 18 5 0 (0.722222222 0.277777778)
## 418) ElectricBill< 195 6 0 0 (1.000000000 0.000000000) *
## 419) ElectricBill>=195 12 5 0 (0.583333333 0.416666667)
## 838) ElectricBill>=255 6 1 0 (0.833333333 0.166666667)
## 1676) NumChildren< 1.5 4 0 0 (1.000000000 0.000000000) *
## 1677) NumChildren>=1.5 2 1 0 (0.500000000 0.500000000)
## 3354) Insurance>=3050 1 0 0 (1.000000000 0.000000000) *
## 3355) Insurance< 3050 1 0 1 (0.000000000 1.000000000) *
## 839) ElectricBill< 255 6 2 1 (0.333333333 0.666666667)
## 1678) ElectricBill< 235 4 2 0 (0.500000000 0.500000000)
## 3356) HouseCosts>=3950 2 0 0 (1.000000000 0.000000000) *
## 3357) HouseCosts< 3950 2 0 1 (0.000000000 1.000000000) *
## 1679) ElectricBill>=235 2 0 1 (0.000000000 1.000000000) *
## 105) Insurance< 1950 1 0 1 (0.000000000 1.000000000) *
## 53) NumRooms< 5.5 8 3 1 (0.375000000 0.625000000)
## 106) ElectricBill< 190 2 0 0 (1.000000000 0.000000000) *
## 107) ElectricBill>=190 6 1 1 (0.166666667 0.833333333)
## 214) Insurance< 2350 2 1 0 (0.500000000 0.500000000)
## 428) Insurance>=2100 1 0 0 (1.000000000 0.000000000) *
## 429) Insurance< 2100 1 0 1 (0.000000000 1.000000000) *
## 215) Insurance>=2350 4 0 1 (0.000000000 1.000000000) *
## 27) NumBedrooms>=3.5 184 84 0 (0.543478261 0.456521739)
## 54) NumVehicles< 1.5 29 8 0 (0.724137931 0.275862069)
## 108) Insurance< 3100 16 2 0 (0.875000000 0.125000000)
## 216) ElectricBill< 290 10 0 0 (1.000000000 0.000000000) *
## 217) ElectricBill>=290 6 2 0 (0.666666667 0.333333333)
## 434) ElectricBill>=310 5 1 0 (0.800000000 0.200000000)
## 868) NumWorkers< 1.5 3 0 0 (1.000000000 0.000000000) *
## 869) NumWorkers>=1.5 2 1 0 (0.500000000 0.500000000)
## 1738) Insurance>=2500 1 0 0 (1.000000000 0.000000000) *
## 1739) Insurance< 2500 1 0 1 (0.000000000 1.000000000) *
## 435) ElectricBill< 310 1 0 1 (0.000000000 1.000000000) *
## 109) Insurance>=3100 13 6 0 (0.538461538 0.461538462)
## 218) ElectricBill< 185 5 1 0 (0.800000000 0.200000000)
## 436) NumBedrooms< 6.5 4 0 0 (1.000000000 0.000000000) *
## 437) NumBedrooms>=6.5 1 0 1 (0.000000000 1.000000000) *
## 219) ElectricBill>=185 8 3 1 (0.375000000 0.625000000)
## 438) NumBedrooms>=4.5 4 1 0 (0.750000000 0.250000000)
## 876) HouseCosts>=3900 3 0 0 (1.000000000 0.000000000) *
## 877) HouseCosts< 3900 1 0 1 (0.000000000 1.000000000) *
## 439) NumBedrooms< 4.5 4 0 1 (0.000000000 1.000000000) *
## 55) NumVehicles>=1.5 155 76 0 (0.509677419 0.490322581)
## 110) ElectricBill>=95 149 71 0 (0.523489933 0.476510067)
## 220) NumBedrooms< 4.5 93 38 0 (0.591397849 0.408602151)
## 440) NumRooms< 12.5 91 36 0 (0.604395604 0.395604396)
## 880) ElectricBill< 140 7 1 0 (0.857142857 0.142857143)
## 1760) HouseCosts< 3850 5 0 0 (1.000000000 0.000000000) *
## 1761) HouseCosts>=3850 2 1 0 (0.500000000 0.500000000)
## 3522) ElectricBill>=120 1 0 0 (1.000000000 0.000000000) *
## 3523) ElectricBill< 120 1 0 1 (0.000000000 1.000000000) *
## 881) ElectricBill>=140 84 35 0 (0.583333333 0.416666667)
## 1762) ElectricBill>=160 78 30 0 (0.615384615 0.384615385)
## 3524) ElectricBill< 205 14 2 0 (0.857142857 0.142857143)
## 7048) NumRooms< 8.5 9 0 0 (1.000000000 0.000000000) *
## 7049) NumRooms>=8.5 5 2 0 (0.600000000 0.400000000)
## 14098) NumChildren< 0.5 3 0 0 (1.000000000 0.000000000) *
## 14099) NumChildren>=0.5 2 0 1 (0.000000000 1.000000000) *
## 3525) ElectricBill>=205 64 28 0 (0.562500000 0.437500000)
## 7050) NumPeople< 5.5 62 26 0 (0.580645161 0.419354839)
## 14100) NumPeople>=2.5 51 19 0 (0.627450980 0.372549020)
## 28200) Insurance< 2900 29 8 0 (0.724137931 0.275862069)
## 56400) HouseCosts>=3550 21 4 0 (0.809523810 0.190476190)
## 112800) NumChildren< 1.5 13 1 0 (0.923076923 0.076923077)
## 225600) Insurance< 2350 10 0 0 (1.000000000 0.000000000) *
## 225601) Insurance>=2350 3 1 0 (0.666666667 0.333333333)
## 451202) Insurance>=2450 2 0 0 (1.000000000 0.000000000) *
## 451203) Insurance< 2450 1 0 1 (0.000000000 1.000000000) *
## 112801) NumChildren>=1.5 8 3 0 (0.625000000 0.375000000)
## 225602) NumWorkers>=1.5 6 1 0 (0.833333333 0.166666667)
## 451204) Insurance>=2050 4 0 0 (1.000000000 0.000000000) *
## 451205) Insurance< 2050 2 1 0 (0.500000000 0.500000000)
## 902410) ElectricBill< 295 1 0 0 (1.000000000 0.000000000) *
## 902411) ElectricBill>=295 1 0 1 (0.000000000 1.000000000) *
## 225603) NumWorkers< 1.5 2 0 1 (0.000000000 1.000000000) *
## 56401) HouseCosts< 3550 8 4 0 (0.500000000 0.500000000)
## 112802) Insurance>=2300 5 1 0 (0.800000000 0.200000000)
## 225604) NumChildren>=1 4 0 0 (1.000000000 0.000000000) *
## 225605) NumChildren< 1 1 0 1 (0.000000000 1.000000000) *
## 112803) Insurance< 2300 3 0 1 (0.000000000 1.000000000) *
## 28201) Insurance>=2900 22 11 0 (0.500000000 0.500000000)
## 56402) NumChildren< 0.5 6 1 0 (0.833333333 0.166666667)
## 112804) HouseCosts>=3550 5 0 0 (1.000000000 0.000000000) *
## 112805) HouseCosts< 3550 1 0 1 (0.000000000 1.000000000) *
## 56403) NumChildren>=0.5 16 6 1 (0.375000000 0.625000000)
## 112806) Insurance>=3650 9 3 0 (0.666666667 0.333333333)
## 225612) ElectricBill>=335 7 1 0 (0.857142857 0.142857143)
## 451224) NumRooms>=6.5 6 0 0 (1.000000000 0.000000000) *
## 451225) NumRooms< 6.5 1 0 1 (0.000000000 1.000000000) *
## 225613) ElectricBill< 335 2 0 1 (0.000000000 1.000000000) *
## 112807) Insurance< 3650 7 0 1 (0.000000000 1.000000000) *
## 14101) NumPeople< 2.5 11 4 1 (0.363636364 0.636363636)
## 28202) Insurance>=3500 2 0 0 (1.000000000 0.000000000) *
## 28203) Insurance< 3500 9 2 1 (0.222222222 0.777777778)
## 56406) HouseCosts>=4350 1 0 0 (1.000000000 0.000000000) *
## 56407) HouseCosts< 4350 8 1 1 (0.125000000 0.875000000)
## 112814) Insurance< 2150 2 1 0 (0.500000000 0.500000000)
## 225628) Insurance>=2050 1 0 0 (1.000000000 0.000000000) *
## 225629) Insurance< 2050 1 0 1 (0.000000000 1.000000000) *
## 112815) Insurance>=2150 6 0 1 (0.000000000 1.000000000) *
## 7051) NumPeople>=5.5 2 0 1 (0.000000000 1.000000000) *
## 1763) ElectricBill< 160 6 1 1 (0.166666667 0.833333333)
## 3526) Insurance>=3250 1 0 0 (1.000000000 0.000000000) *
## 3527) Insurance< 3250 5 0 1 (0.000000000 1.000000000) *
## 441) NumRooms>=12.5 2 0 1 (0.000000000 1.000000000) *
## 221) NumBedrooms>=4.5 56 23 1 (0.410714286 0.589285714)
## 442) Insurance>=2450 49 22 1 (0.448979592 0.551020408)
## 884) ElectricBill>=510 6 1 0 (0.833333333 0.166666667)
## 1768) HouseCosts>=3750 4 0 0 (1.000000000 0.000000000) *
## 1769) HouseCosts< 3750 2 1 0 (0.500000000 0.500000000)
## 3538) NumBedrooms< 6.5 1 0 0 (1.000000000 0.000000000) *
## 3539) NumBedrooms>=6.5 1 0 1 (0.000000000 1.000000000) *
## 885) ElectricBill< 510 43 17 1 (0.395348837 0.604651163)
## 1770) ElectricBill< 475 36 16 1 (0.444444444 0.555555556)
## 3540) Insurance>=5550 7 2 0 (0.714285714 0.285714286)
## 7080) NumRooms< 12.5 5 0 0 (1.000000000 0.000000000) *
## 7081) NumRooms>=12.5 2 0 1 (0.000000000 1.000000000) *
## 3541) Insurance< 5550 29 11 1 (0.379310345 0.620689655)
## 7082) NumBedrooms>=6.5 9 3 0 (0.666666667 0.333333333)
## 14164) Insurance< 3900 7 1 0 (0.857142857 0.142857143)
## 28328) NumWorkers>=1.5 6 0 0 (1.000000000 0.000000000) *
## 28329) NumWorkers< 1.5 1 0 1 (0.000000000 1.000000000) *
## 14165) Insurance>=3900 2 0 1 (0.000000000 1.000000000) *
## 7083) NumBedrooms< 6.5 20 5 1 (0.250000000 0.750000000)
## 14166) NumPeople< 4.5 14 5 1 (0.357142857 0.642857143)
## 28332) NumPeople>=3.5 6 2 0 (0.666666667 0.333333333)
## 56664) ElectricBill>=225 5 1 0 (0.800000000 0.200000000)
## 113328) NumWorkers< 2.5 4 0 0 (1.000000000 0.000000000) *
## 113329) NumWorkers>=2.5 1 0 1 (0.000000000 1.000000000) *
## 56665) ElectricBill< 225 1 0 1 (0.000000000 1.000000000) *
## 28333) NumPeople< 3.5 8 1 1 (0.125000000 0.875000000)
## 56666) HouseCosts< 3850 2 1 0 (0.500000000 0.500000000)
## 113332) Insurance< 3500 1 0 0 (1.000000000 0.000000000) *
## 113333) Insurance>=3500 1 0 1 (0.000000000 1.000000000) *
## 56667) HouseCosts>=3850 6 0 1 (0.000000000 1.000000000) *
## 14167) NumPeople>=4.5 6 0 1 (0.000000000 1.000000000) *
## 1771) ElectricBill>=475 7 1 1 (0.142857143 0.857142857)
## 3542) NumRooms>=10.5 2 1 0 (0.500000000 0.500000000)
## 7084) NumPeople< 4.5 1 0 0 (1.000000000 0.000000000) *
## 7085) NumPeople>=4.5 1 0 1 (0.000000000 1.000000000) *
## 3543) NumRooms< 10.5 5 0 1 (0.000000000 1.000000000) *
## 443) Insurance< 2450 7 1 1 (0.142857143 0.857142857)
## 886) HouseCosts< 3750 2 1 0 (0.500000000 0.500000000)
## 1772) ElectricBill< 440 1 0 0 (1.000000000 0.000000000) *
## 1773) ElectricBill>=440 1 0 1 (0.000000000 1.000000000) *
## 887) HouseCosts>=3750 5 0 1 (0.000000000 1.000000000) *
## 111) ElectricBill< 95 6 1 1 (0.166666667 0.833333333)
## 222) NumBedrooms>=6 1 0 0 (1.000000000 0.000000000) *
## 223) NumBedrooms< 6 5 0 1 (0.000000000 1.000000000) *
## 7) HouseCosts>=4450 403 176 1 (0.436724566 0.563275434)
## 14) ElectricBill< 430 326 156 1 (0.478527607 0.521472393)
## 28) Insurance< 865 20 3 0 (0.850000000 0.150000000)
## 56) NumChildren< 0.5 8 0 0 (1.000000000 0.000000000) *
## 57) NumChildren>=0.5 12 3 0 (0.750000000 0.250000000)
## 114) Insurance>=750 4 0 0 (1.000000000 0.000000000) *
## 115) Insurance< 750 8 3 0 (0.625000000 0.375000000)
## 230) HouseCosts< 5650 3 0 0 (1.000000000 0.000000000) *
## 231) HouseCosts>=5650 5 2 1 (0.400000000 0.600000000)
## 462) ElectricBill< 235 3 1 0 (0.666666667 0.333333333)
## 924) Insurance< 600 2 0 0 (1.000000000 0.000000000) *
## 925) Insurance>=600 1 0 1 (0.000000000 1.000000000) *
## 463) ElectricBill>=235 2 0 1 (0.000000000 1.000000000) *
## 29) Insurance>=865 306 139 1 (0.454248366 0.545751634)
## 58) NumRooms< 5.5 20 5 0 (0.750000000 0.250000000)
## 116) Insurance< 3650 15 2 0 (0.866666667 0.133333333)
## 232) ElectricBill>=190 6 0 0 (1.000000000 0.000000000) *
## 233) ElectricBill< 190 9 2 0 (0.777777778 0.222222222)
## 466) HouseCosts>=4550 8 1 0 (0.875000000 0.125000000)
## 932) ElectricBill< 175 6 0 0 (1.000000000 0.000000000) *
## 933) ElectricBill>=175 2 1 0 (0.500000000 0.500000000)
## 1866) Insurance< 1850 1 0 0 (1.000000000 0.000000000) *
## 1867) Insurance>=1850 1 0 1 (0.000000000 1.000000000) *
## 467) HouseCosts< 4550 1 0 1 (0.000000000 1.000000000) *
## 117) Insurance>=3650 5 2 1 (0.400000000 0.600000000)
## 234) Insurance>=4250 3 1 0 (0.666666667 0.333333333)
## 468) NumBedrooms>=2.5 2 0 0 (1.000000000 0.000000000) *
## 469) NumBedrooms< 2.5 1 0 1 (0.000000000 1.000000000) *
## 235) Insurance< 4250 2 0 1 (0.000000000 1.000000000) *
## 59) NumRooms>=5.5 286 124 1 (0.433566434 0.566433566)
## 118) NumPeople>=6.5 7 1 0 (0.857142857 0.142857143)
## 236) ElectricBill>=265 6 0 0 (1.000000000 0.000000000) *
## 237) ElectricBill< 265 1 0 1 (0.000000000 1.000000000) *
## 119) NumPeople< 6.5 279 118 1 (0.422939068 0.577060932)
## 238) NumRooms< 8.5 114 57 0 (0.500000000 0.500000000)
## 476) NumPeople>=3.5 67 27 0 (0.597014925 0.402985075)
## 952) NumVehicles>=3.5 6 0 0 (1.000000000 0.000000000) *
## 953) NumVehicles< 3.5 61 27 0 (0.557377049 0.442622951)
## 1906) NumWorkers< 1.5 22 6 0 (0.727272727 0.272727273)
## 3812) ElectricBill>=315 6 0 0 (1.000000000 0.000000000) *
## 3813) ElectricBill< 315 16 6 0 (0.625000000 0.375000000)
## 7626) NumRooms< 6.5 4 0 0 (1.000000000 0.000000000) *
## 7627) NumRooms>=6.5 12 6 0 (0.500000000 0.500000000)
## 15254) Insurance>=1600 9 3 0 (0.666666667 0.333333333)
## 30508) NumRooms>=7.5 6 0 0 (1.000000000 0.000000000) *
## 30509) NumRooms< 7.5 3 0 1 (0.000000000 1.000000000) *
## 15255) Insurance< 1600 3 0 1 (0.000000000 1.000000000) *
## 1907) NumWorkers>=1.5 39 18 1 (0.461538462 0.538461538)
## 3814) Insurance< 1450 9 1 0 (0.888888889 0.111111111)
## 7628) Insurance>=950 7 0 0 (1.000000000 0.000000000) *
## 7629) Insurance< 950 2 1 0 (0.500000000 0.500000000)
## 15258) ElectricBill>=260 1 0 0 (1.000000000 0.000000000) *
## 15259) ElectricBill< 260 1 0 1 (0.000000000 1.000000000) *
## 3815) Insurance>=1450 30 10 1 (0.333333333 0.666666667)
## 7630) NumChildren< 1.5 10 4 0 (0.600000000 0.400000000)
## 15260) NumVehicles< 2.5 6 1 0 (0.833333333 0.166666667)
## 30520) ElectricBill< 375 5 0 0 (1.000000000 0.000000000) *
## 30521) ElectricBill>=375 1 0 1 (0.000000000 1.000000000) *
## 15261) NumVehicles>=2.5 4 1 1 (0.250000000 0.750000000)
## 30522) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 30523) NumBedrooms>=3.5 3 0 1 (0.000000000 1.000000000) *
## 7631) NumChildren>=1.5 20 4 1 (0.200000000 0.800000000)
## 15262) Insurance>=3700 4 2 0 (0.500000000 0.500000000)
## 30524) ElectricBill>=215 2 0 0 (1.000000000 0.000000000) *
## 30525) ElectricBill< 215 2 0 1 (0.000000000 1.000000000) *
## 15263) Insurance< 3700 16 2 1 (0.125000000 0.875000000)
## 30526) NumChildren>=2.5 6 2 1 (0.333333333 0.666666667)
## 61052) ElectricBill< 225 1 0 0 (1.000000000 0.000000000) *
## 61053) ElectricBill>=225 5 1 1 (0.200000000 0.800000000)
## 122106) ElectricBill>=325 1 0 0 (1.000000000 0.000000000) *
## 122107) ElectricBill< 325 4 0 1 (0.000000000 1.000000000) *
## 30527) NumChildren< 2.5 10 0 1 (0.000000000 1.000000000) *
## 477) NumPeople< 3.5 47 17 1 (0.361702128 0.638297872)
## 954) NumPeople< 2.5 25 11 0 (0.560000000 0.440000000)
## 1908) ElectricBill>=260 7 1 0 (0.857142857 0.142857143)
## 3816) ElectricBill< 345 6 0 0 (1.000000000 0.000000000) *
## 3817) ElectricBill>=345 1 0 1 (0.000000000 1.000000000) *
## 1909) ElectricBill< 260 18 8 1 (0.444444444 0.555555556)
## 3818) NumVehicles>=1.5 12 5 0 (0.583333333 0.416666667)
## 7636) ElectricBill< 110 2 0 0 (1.000000000 0.000000000) *
## 7637) ElectricBill>=110 10 5 0 (0.500000000 0.500000000)
## 15274) Insurance>=990 9 4 0 (0.555555556 0.444444444)
## 30548) HouseCosts< 4750 2 0 0 (1.000000000 0.000000000) *
## 30549) HouseCosts>=4750 7 3 1 (0.428571429 0.571428571)
## 61098) NumWorkers>=1.5 2 0 0 (1.000000000 0.000000000) *
## 61099) NumWorkers< 1.5 5 1 1 (0.200000000 0.800000000)
## 122198) ElectricBill< 165 2 1 0 (0.500000000 0.500000000)
## 244396) Insurance< 3950 1 0 0 (1.000000000 0.000000000) *
## 244397) Insurance>=3950 1 0 1 (0.000000000 1.000000000) *
## 122199) ElectricBill>=165 3 0 1 (0.000000000 1.000000000) *
## 15275) Insurance< 990 1 0 1 (0.000000000 1.000000000) *
## 3819) NumVehicles< 1.5 6 1 1 (0.166666667 0.833333333)
## 7638) NumVehicles< 0.5 1 0 0 (1.000000000 0.000000000) *
## 7639) NumVehicles>=0.5 5 0 1 (0.000000000 1.000000000) *
## 955) NumPeople>=2.5 22 3 1 (0.136363636 0.863636364)
## 1910) Insurance< 3250 13 3 1 (0.230769231 0.769230769)
## 3820) Insurance>=2500 1 0 0 (1.000000000 0.000000000) *
## 3821) Insurance< 2500 12 2 1 (0.166666667 0.833333333)
## 7642) HouseCosts< 4600 2 1 0 (0.500000000 0.500000000)
## 15284) Insurance< 1150 1 0 0 (1.000000000 0.000000000) *
## 15285) Insurance>=1150 1 0 1 (0.000000000 1.000000000) *
## 7643) HouseCosts>=4600 10 1 1 (0.100000000 0.900000000)
## 15286) NumBedrooms>=4.5 3 1 1 (0.333333333 0.666666667)
## 30572) ElectricBill< 290 1 0 0 (1.000000000 0.000000000) *
## 30573) ElectricBill>=290 2 0 1 (0.000000000 1.000000000) *
## 15287) NumBedrooms< 4.5 7 0 1 (0.000000000 1.000000000) *
## 1911) Insurance>=3250 9 0 1 (0.000000000 1.000000000) *
## 239) NumRooms>=8.5 165 61 1 (0.369696970 0.630303030)
## 478) ElectricBill< 105 21 9 0 (0.571428571 0.428571429)
## 956) ElectricBill>=55 16 5 0 (0.687500000 0.312500000)
## 1912) NumVehicles>=2.5 4 0 0 (1.000000000 0.000000000) *
## 1913) NumVehicles< 2.5 12 5 0 (0.583333333 0.416666667)
## 3826) Insurance< 1050 2 0 0 (1.000000000 0.000000000) *
## 3827) Insurance>=1050 10 5 0 (0.500000000 0.500000000)
## 7654) Insurance>=1500 8 3 0 (0.625000000 0.375000000)
## 15308) NumChildren< 3.5 7 2 0 (0.714285714 0.285714286)
## 30616) NumChildren>=1.5 3 0 0 (1.000000000 0.000000000) *
## 30617) NumChildren< 1.5 4 2 0 (0.500000000 0.500000000)
## 61234) Insurance< 1900 1 0 0 (1.000000000 0.000000000) *
## 61235) Insurance>=1900 3 1 1 (0.333333333 0.666666667)
## 122470) Insurance>=5700 1 0 0 (1.000000000 0.000000000) *
## 122471) Insurance< 5700 2 0 1 (0.000000000 1.000000000) *
## 15309) NumChildren>=3.5 1 0 1 (0.000000000 1.000000000) *
## 7655) Insurance< 1500 2 0 1 (0.000000000 1.000000000) *
## 957) ElectricBill< 55 5 1 1 (0.200000000 0.800000000)
## 1914) NumPeople< 3.5 1 0 0 (1.000000000 0.000000000) *
## 1915) NumPeople>=3.5 4 0 1 (0.000000000 1.000000000) *
## 479) ElectricBill>=105 144 49 1 (0.340277778 0.659722222)
## 958) ElectricBill>=380 19 8 0 (0.578947368 0.421052632)
## 1916) Insurance< 2750 7 1 0 (0.857142857 0.142857143)
## 3832) Insurance>=1200 6 0 0 (1.000000000 0.000000000) *
## 3833) Insurance< 1200 1 0 1 (0.000000000 1.000000000) *
## 1917) Insurance>=2750 12 5 1 (0.416666667 0.583333333)
## 3834) Insurance>=3800 9 4 0 (0.555555556 0.444444444)
## 7668) Insurance< 5700 3 0 0 (1.000000000 0.000000000) *
## 7669) Insurance>=5700 6 2 1 (0.333333333 0.666666667)
## 15338) NumWorkers>=1.5 2 0 0 (1.000000000 0.000000000) *
## 15339) NumWorkers< 1.5 4 0 1 (0.000000000 1.000000000) *
## 3835) Insurance< 3800 3 0 1 (0.000000000 1.000000000) *
## 959) ElectricBill< 380 125 38 1 (0.304000000 0.696000000)
## 1918) NumChildren< 2.5 99 35 1 (0.353535354 0.646464646)
## 3836) NumPeople>=5.5 3 0 0 (1.000000000 0.000000000) *
## 3837) NumPeople< 5.5 96 32 1 (0.333333333 0.666666667)
## 7674) Insurance< 2050 29 14 1 (0.482758621 0.517241379)
## 15348) NumVehicles>=3.5 4 0 0 (1.000000000 0.000000000) *
## 15349) NumVehicles< 3.5 25 10 1 (0.400000000 0.600000000)
## 30698) ElectricBill< 265 15 6 0 (0.600000000 0.400000000)
## 61396) Insurance>=1550 7 1 0 (0.857142857 0.142857143)
## 122792) HouseCosts>=4600 6 0 0 (1.000000000 0.000000000) *
## 122793) HouseCosts< 4600 1 0 1 (0.000000000 1.000000000) *
## 61397) Insurance< 1550 8 3 1 (0.375000000 0.625000000)
## 122794) Insurance< 950 1 0 0 (1.000000000 0.000000000) *
## 122795) Insurance>=950 7 2 1 (0.285714286 0.714285714)
## 245590) HouseCosts>=4850 4 2 0 (0.500000000 0.500000000)
## 491180) Insurance< 1300 3 1 0 (0.666666667 0.333333333)
## 982360) NumBedrooms>=3.5 2 0 0 (1.000000000 0.000000000) *
## 982361) NumBedrooms< 3.5 1 0 1 (0.000000000 1.000000000) *
## 491181) Insurance>=1300 1 0 1 (0.000000000 1.000000000) *
## 245591) HouseCosts< 4850 3 0 1 (0.000000000 1.000000000) *
## 30699) ElectricBill>=265 10 1 1 (0.100000000 0.900000000)
## 61398) Insurance< 1150 1 0 0 (1.000000000 0.000000000) *
## 61399) Insurance>=1150 9 0 1 (0.000000000 1.000000000) *
## 7675) Insurance>=2050 67 18 1 (0.268656716 0.731343284)
## 15350) Insurance>=2800 57 18 1 (0.315789474 0.684210526)
## 30700) FoodStamp=Yes 1 0 0 (1.000000000 0.000000000) *
## 30701) FoodStamp=No 56 17 1 (0.303571429 0.696428571)
## 61402) NumRooms< 11.5 38 14 1 (0.368421053 0.631578947)
## 122804) ElectricBill>=345 6 2 0 (0.666666667 0.333333333)
## 245608) Insurance>=3100 5 1 0 (0.800000000 0.200000000)
## 491216) NumVehicles< 3.5 4 0 0 (1.000000000 0.000000000) *
## 491217) NumVehicles>=3.5 1 0 1 (0.000000000 1.000000000) *
## 245609) Insurance< 3100 1 0 1 (0.000000000 1.000000000) *
## 122805) ElectricBill< 345 32 10 1 (0.312500000 0.687500000)
## 245610) NumVehicles< 1.5 2 0 0 (1.000000000 0.000000000) *
## 245611) NumVehicles>=1.5 30 8 1 (0.266666667 0.733333333)
## 491222) NumPeople>=2.5 25 8 1 (0.320000000 0.680000000)
## 982444) ElectricBill< 195 6 2 0 (0.666666667 0.333333333)
## 1964888) Insurance>=3200 4 0 0 (1.000000000 0.000000000) *
## 1964889) Insurance< 3200 2 0 1 (0.000000000 1.000000000) *
## 982445) ElectricBill>=195 19 4 1 (0.210526316 0.789473684)
## 1964890) NumPeople>=3.5 9 3 1 (0.333333333 0.666666667)
## 3929780) NumBedrooms< 3.5 1 0 0 (1.000000000 0.000000000) *
## 3929781) NumBedrooms>=3.5 8 2 1 (0.250000000 0.750000000)
## 7859562) NumChildren< 0.5 1 0 0 (1.000000000 0.000000000) *
## 7859563) NumChildren>=0.5 7 1 1 (0.142857143 0.857142857)
## 15719126) Insurance>=5300 2 1 0 (0.500000000 0.500000000)
## 31438252) ElectricBill>=275 1 0 0 (1.000000000 0.000000000) *
## 31438253) ElectricBill< 275 1 0 1 (0.000000000 1.000000000) *
## 15719127) Insurance< 5300 5 0 1 (0.000000000 1.000000000) *
## 1964891) NumPeople< 3.5 10 1 1 (0.100000000 0.900000000)
## 3929782) ElectricBill< 235 4 1 1 (0.250000000 0.750000000)
## 7859564) Insurance>=5300 2 1 0 (0.500000000 0.500000000)
## 15719128) NumChildren< 0.5 1 0 0 (1.000000000 0.000000000) *
## 15719129) NumChildren>=0.5 1 0 1 (0.000000000 1.000000000) *
## 7859565) Insurance< 5300 2 0 1 (0.000000000 1.000000000) *
## 3929783) ElectricBill>=235 6 0 1 (0.000000000 1.000000000) *
## 491223) NumPeople< 2.5 5 0 1 (0.000000000 1.000000000) *
## 61403) NumRooms>=11.5 18 3 1 (0.166666667 0.833333333)
## 122806) ElectricBill< 170 2 1 0 (0.500000000 0.500000000)
## 245612) ElectricBill>=140 1 0 0 (1.000000000 0.000000000) *
## 245613) ElectricBill< 140 1 0 1 (0.000000000 1.000000000) *
## 122807) ElectricBill>=170 16 2 1 (0.125000000 0.875000000)
## 245614) Insurance< 4650 3 1 1 (0.333333333 0.666666667)
## 491228) Insurance>=4250 1 0 0 (1.000000000 0.000000000) *
## 491229) Insurance< 4250 2 0 1 (0.000000000 1.000000000) *
## 245615) Insurance>=4650 13 1 1 (0.076923077 0.923076923)
## 491230) ElectricBill>=225 7 1 1 (0.142857143 0.857142857)
## 982460) ElectricBill< 275 1 0 0 (1.000000000 0.000000000) *
## 982461) ElectricBill>=275 6 0 1 (0.000000000 1.000000000) *
## 491231) ElectricBill< 225 6 0 1 (0.000000000 1.000000000) *
## 15351) Insurance< 2800 10 0 1 (0.000000000 1.000000000) *
## 1919) NumChildren>=2.5 26 3 1 (0.115384615 0.884615385)
## 3838) ElectricBill< 155 6 2 1 (0.333333333 0.666666667)
## 7676) NumWorkers>=1.5 3 1 0 (0.666666667 0.333333333)
## 15352) Insurance>=1650 2 0 0 (1.000000000 0.000000000) *
## 15353) Insurance< 1650 1 0 1 (0.000000000 1.000000000) *
## 7677) NumWorkers< 1.5 3 0 1 (0.000000000 1.000000000) *
## 3839) ElectricBill>=155 20 1 1 (0.050000000 0.950000000)
## 7678) HouseCosts< 5650 2 1 0 (0.500000000 0.500000000)
## 15356) Insurance>=3300 1 0 0 (1.000000000 0.000000000) *
## 15357) Insurance< 3300 1 0 1 (0.000000000 1.000000000) *
## 7679) HouseCosts>=5650 18 0 1 (0.000000000 1.000000000) *
## 15) ElectricBill>=430 77 20 1 (0.259740260 0.740259740)
## 30) NumRooms< 10.5 48 17 1 (0.354166667 0.645833333)
## 60) NumWorkers< 1.5 17 8 0 (0.529411765 0.470588235)
## 120) NumChildren< 2.5 14 5 0 (0.642857143 0.357142857)
## 240) NumVehicles>=1.5 10 2 0 (0.800000000 0.200000000)
## 480) Insurance>=260 9 1 0 (0.888888889 0.111111111)
## 960) NumChildren>=0.5 6 0 0 (1.000000000 0.000000000) *
## 961) NumChildren< 0.5 3 1 0 (0.666666667 0.333333333)
## 1922) NumPeople< 3.5 2 0 0 (1.000000000 0.000000000) *
## 1923) NumPeople>=3.5 1 0 1 (0.000000000 1.000000000) *
## 481) Insurance< 260 1 0 1 (0.000000000 1.000000000) *
## 241) NumVehicles< 1.5 4 1 1 (0.250000000 0.750000000)
## 482) NumChildren>=1.5 1 0 0 (1.000000000 0.000000000) *
## 483) NumChildren< 1.5 3 0 1 (0.000000000 1.000000000) *
## 121) NumChildren>=2.5 3 0 1 (0.000000000 1.000000000) *
## 61) NumWorkers>=1.5 31 8 1 (0.258064516 0.741935484)
## 122) NumBedrooms< 4.5 19 8 1 (0.421052632 0.578947368)
## 244) Insurance< 2200 7 2 0 (0.714285714 0.285714286)
## 488) Insurance>=450 6 1 0 (0.833333333 0.166666667)
## 976) NumVehicles< 3.5 5 0 0 (1.000000000 0.000000000) *
## 977) NumVehicles>=3.5 1 0 1 (0.000000000 1.000000000) *
## 489) Insurance< 450 1 0 1 (0.000000000 1.000000000) *
## 245) Insurance>=2200 12 3 1 (0.250000000 0.750000000)
## 490) NumChildren>=4.5 1 0 0 (1.000000000 0.000000000) *
## 491) NumChildren< 4.5 11 2 1 (0.181818182 0.818181818)
## 982) NumPeople< 2.5 2 1 0 (0.500000000 0.500000000)
## 1964) Insurance< 3250 1 0 0 (1.000000000 0.000000000) *
## 1965) Insurance>=3250 1 0 1 (0.000000000 1.000000000) *
## 983) NumPeople>=2.5 9 1 1 (0.111111111 0.888888889)
## 1966) Insurance>=3900 3 1 1 (0.333333333 0.666666667)
## 3932) NumChildren>=1.5 1 0 0 (1.000000000 0.000000000) *
## 3933) NumChildren< 1.5 2 0 1 (0.000000000 1.000000000) *
## 1967) Insurance< 3900 6 0 1 (0.000000000 1.000000000) *
## 123) NumBedrooms>=4.5 12 0 1 (0.000000000 1.000000000) *
## 31) NumRooms>=10.5 29 3 1 (0.103448276 0.896551724)
## 62) Insurance>=2400 16 3 1 (0.187500000 0.812500000)
## 124) Insurance< 2750 1 0 0 (1.000000000 0.000000000) *
## 125) Insurance>=2750 15 2 1 (0.133333333 0.866666667)
## 250) NumChildren>=2.5 2 1 0 (0.500000000 0.500000000)
## 500) Insurance< 4800 1 0 0 (1.000000000 0.000000000) *
## 501) Insurance>=4800 1 0 1 (0.000000000 1.000000000) *
## 251) NumChildren< 2.5 13 1 1 (0.076923077 0.923076923)
## 502) ElectricBill< 470 5 1 1 (0.200000000 0.800000000)
## 1004) Insurance< 5550 2 1 0 (0.500000000 0.500000000)
## 2008) Insurance>=3750 1 0 0 (1.000000000 0.000000000) *
## 2009) Insurance< 3750 1 0 1 (0.000000000 1.000000000) *
## 1005) Insurance>=5550 3 0 1 (0.000000000 1.000000000) *
## 503) ElectricBill>=470 8 0 1 (0.000000000 1.000000000) *
## 63) Insurance< 2400 13 0 1 (0.000000000 1.000000000) *head(predict(tree4))## 0 1
## 2 1 0
## 3 1 0
## 4 1 0
## 5 1 0
## 7 1 0
## 9 1 0head(predict(tree4, type="class"))## 2 3 4 5 7 9
## 0 0 0 0 0 0
## Levels: 0 1tree4_cm <- confusionMatrix(predict(tree4, type="class"), acs_fit$HighIncome, positive = "1")
tree4_cm## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 17079 1
## 1 0 1116
##
## Accuracy : 0.9999
## 95% CI : (0.9997, 1)
## No Information Rate : 0.9386
## P-Value [Acc > NIR] : <2e-16
##
## Kappa : 0.9995
## Mcnemar's Test P-Value : 1
##
## Sensitivity : 0.99910
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.99994
## Prevalence : 0.06139
## Detection Rate : 0.06133
## Detection Prevalence : 0.06133
## Balanced Accuracy : 0.99955
##
## 'Positive' Class : 1
## Tree Comparison
# make predictions using test data
tree1_pred <- predict(tree1, acs_test, type="class" )
tree2_pred <- predict(tree2, acs_test, type="class" )
tree3_pred <- predict(tree3, acs_test, type="class" )
tree4_pred <- predict(tree4, acs_test, type="class" )
# Confusion matrices
tree_cm1_pred <- confusionMatrix(tree1_pred, acs_test$HighIncome, positive = "1")
tree_cm2_pred <- confusionMatrix(tree2_pred, acs_test$HighIncome, positive = "1")
tree_cm3_pred <- confusionMatrix(tree3_pred, acs_test$HighIncome, positive = "1")
tree_cm4_pred <- confusionMatrix(tree4_pred, acs_test$HighIncome, positive = "1")
# Display comparison of accuracy of each decision tree
sprintf("Tree1: Fit acc = %.3f Pred acc = %.3f",tree1_cm$overall['Accuracy'], tree_cm1_pred$overall['Accuracy'])## [1] "Tree1: Fit acc = 0.941 Pred acc = 0.942"sprintf("Tree2: Fit acc = %.3f Pred acc = %.3f",tree2_cm$overall['Accuracy'], tree_cm2_pred$overall['Accuracy'])## [1] "Tree2: Fit acc = 0.939 Pred acc = 0.939"sprintf("Tree3: Fit acc = %.3f Pred acc = %.3f",tree3_cm$overall['Accuracy'], tree_cm3_pred$overall['Accuracy'])## [1] "Tree3: Fit acc = 0.943 Pred acc = 0.943"sprintf("Tree4: Fit acc = %.3f Pred acc = %.3f",tree4_cm$overall['Accuracy'], tree_cm4_pred$overall['Accuracy'])## [1] "Tree4: Fit acc = 1.000 Pred acc = 0.896"Decision Tree Decision
- At first glance tree 4 would appear the best choice. However, this tree has a nearly 100% accuracy in the fit data BUT the lowest prediction accuracy. This can be seen through its extreme complexity which leads to a .99 sensitivity. This is like overfitting that leads to “garbage” predictions unless the samples are nearly identical
- I would choose Tree 3 for two reasons - First, it has highest prediction accuracy. Second, it has a pretty low sensitivity at .14
k-nearest neighbor
First Normalize the dataset
normalize <- function(x) {
num <- x - min(x)
denom <- max(x) - min(x)
return (num/denom)
}acs_numericals <- data.frame(acs$NumBedrooms, acs$NumChildren, acs$NumPeople, acs$NumRooms, acs$NumVehicles, acs$NumWorkers, acs$HouseCosts, acs$ElectricBill, acs$Insurance)
acs_norm <- as.data.frame(lapply(acs_numericals[1:8], normalize))
acs_norm$HighIncome1 <- c(acs$HighIncome)# Count rows
m <- nrow(acs_numericals)
# Create index of random row nums for the validation set
val <- sample(1:m, size = round(m/3))
# Create the learning and validation sets
acsNorm_learn <- acs_norm[-val,]
acsNorm_valid <- acs_norm[val,]summary(acs_norm)## acs.NumBedrooms acs.NumChildren acs.NumPeople acs.NumRooms
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.3750 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.2500
## Median :0.3750 Median :0.0000 Median :0.0625 Median :0.3000
## Mean :0.4232 Mean :0.0751 Mean :0.0869 Mean :0.3087
## 3rd Qu.:0.5000 3rd Qu.:0.1667 3rd Qu.:0.1250 3rd Qu.:0.3500
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## acs.NumVehicles acs.NumWorkers acs.HouseCosts acs.ElectricBill
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.3333 1st Qu.:0.3333 1st Qu.:0.09117 1st Qu.:0.1710
## Median :0.3333 Median :0.6667 Median :0.16878 Median :0.2573
## Mean :0.3521 Mean :0.5815 Mean :0.20836 Mean :0.3006
## 3rd Qu.:0.5000 3rd Qu.:0.6667 3rd Qu.:0.28168 3rd Qu.:0.3782
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## HighIncome1
## Min. :0.00000
## 1st Qu.:0.00000
## Median :0.00000
## Mean :0.06107
## 3rd Qu.:0.00000
## Max. :1.00000knn 1
acs_knn1 <- knn(acsNorm_learn[,1:8], acsNorm_valid[,1:8], acsNorm_learn$HighIncome1, k=5, prob = TRUE)
head(acs_knn1)## [1] 0 0 0 0 0 0
## Levels: 0 1# Show the classification matrix
table(acsNorm_valid$HighIncome1, acs_knn1)## acs_knn1
## 0 1
## 0 7020 91
## 1 390 81pcol1 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[1:8], pch = pcol1, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn1)+1])
# confusion matrix for knn1
knn1_cm1_pred <- confusionMatrix(acs_knn1, acsNorm_valid$HighIncome, positive = "1")
knn1_cm1_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7020 390
## 1 91 81
##
## Accuracy : 0.9366
## 95% CI : (0.9308, 0.9419)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.6931
##
## Kappa : 0.2262
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.17197
## Specificity : 0.98720
## Pos Pred Value : 0.47093
## Neg Pred Value : 0.94737
## Prevalence : 0.06212
## Detection Rate : 0.01068
## Detection Prevalence : 0.02269
## Balanced Accuracy : 0.57959
##
## 'Positive' Class : 1
## # confusion matrix for knn1
knn1_cm1_pred <- confusionMatrix(acs_knn1, acsNorm_valid$HighIncome, positive = "1")
knn1_cm1_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7020 390
## 1 91 81
##
## Accuracy : 0.9366
## 95% CI : (0.9308, 0.9419)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.6931
##
## Kappa : 0.2262
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.17197
## Specificity : 0.98720
## Pos Pred Value : 0.47093
## Neg Pred Value : 0.94737
## Prevalence : 0.06212
## Detection Rate : 0.01068
## Detection Prevalence : 0.02269
## Balanced Accuracy : 0.57959
##
## 'Positive' Class : 1
## knn 2
acs_knn2 <- knn(acsNorm_learn[,1:4], acsNorm_valid[,1:4], acsNorm_learn$HighIncome, k=5, prob = TRUE)
head(acs_knn2)## [1] 0 0 0 0 0 0
## Levels: 0 1table(acsNorm_valid$HighIncome, acs_knn2)## acs_knn2
## 0 1
## 0 7089 22
## 1 458 13pcol2 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[2:5], pch = pcol2, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn2)+1])
knn2_cm2_pred <- confusionMatrix(acs_knn2, acsNorm_valid$HighIncome, positive = "1")
knn2_cm2_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7089 458
## 1 22 13
##
## Accuracy : 0.9367
## 95% CI : (0.931, 0.9421)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.6763
##
## Kappa : 0.0432
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.027601
## Specificity : 0.996906
## Pos Pred Value : 0.371429
## Neg Pred Value : 0.939314
## Prevalence : 0.062121
## Detection Rate : 0.001715
## Detection Prevalence : 0.004616
## Balanced Accuracy : 0.512254
##
## 'Positive' Class : 1
## knn 3
acs_knn3 <- knn(acsNorm_learn[,6:8], acsNorm_valid[,6:8], acsNorm_learn$HighIncome, k=3, prob = TRUE)
head(acs_knn3)## [1] 0 0 0 0 0 0
## Levels: 0 1table(acsNorm_valid$HighIncome, acs_knn3)## acs_knn3
## 0 1
## 0 7003 108
## 1 399 72pcol3 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[6:8], pch = pcol3, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn3)+1])
knn3_cm3_pred <- confusionMatrix(acs_knn3, acsNorm_valid$HighIncome, positive = "1")
knn3_cm3_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7003 399
## 1 108 72
##
## Accuracy : 0.9331
## 95% CI : (0.9273, 0.9387)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.9576
##
## Kappa : 0.1935
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.152866
## Specificity : 0.984812
## Pos Pred Value : 0.400000
## Neg Pred Value : 0.946096
## Prevalence : 0.062121
## Detection Rate : 0.009496
## Detection Prevalence : 0.023740
## Balanced Accuracy : 0.568839
##
## 'Positive' Class : 1
## knn 4
acs_knn4 <- knn(acsNorm_learn[,1:8], acsNorm_valid[,1:8], acsNorm_learn$HighIncome, k=10, prob = TRUE)
head(acs_knn4)## [1] 0 0 0 0 0 0
## Levels: 0 1table(acsNorm_valid$HighIncome, acs_knn4)## acs_knn4
## 0 1
## 0 7053 58
## 1 411 60pcol4 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[1:8], pch = pcol4, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn4)+1])
knn4_cm4_pred <- confusionMatrix(acs_knn4, acsNorm_valid$HighIncome, positive = "1")
knn4_cm4_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7053 411
## 1 58 60
##
## Accuracy : 0.9381
## 95% CI : (0.9325, 0.9435)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.4743
##
## Kappa : 0.1834
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.127389
## Specificity : 0.991844
## Pos Pred Value : 0.508475
## Neg Pred Value : 0.944936
## Prevalence : 0.062121
## Detection Rate : 0.007913
## Detection Prevalence : 0.015563
## Balanced Accuracy : 0.559616
##
## 'Positive' Class : 1
## knn 5
acs_knn5 <- knn(acsNorm_learn[,1:8], acsNorm_valid[,1:8], acsNorm_learn$HighIncome, k=20, prob = TRUE)
head(acs_knn5)## [1] 0 0 0 0 0 0
## Levels: 0 1table(acsNorm_valid$HighIncome, acs_knn5)## acs_knn5
## 0 1
## 0 7072 39
## 1 411 60pcol5 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[1:8], pch = pcol5, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn5)+1])
knn5_cm5_pred <- confusionMatrix(acs_knn5, acsNorm_valid$HighIncome, positive = "1")
knn5_cm5_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7072 411
## 1 39 60
##
## Accuracy : 0.9406
## 95% CI : (0.9351, 0.9459)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.1648
##
## Kappa : 0.1931
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.127389
## Specificity : 0.994516
## Pos Pred Value : 0.606061
## Neg Pred Value : 0.945076
## Prevalence : 0.062121
## Detection Rate : 0.007913
## Detection Prevalence : 0.013057
## Balanced Accuracy : 0.560952
##
## 'Positive' Class : 1
## knn 6
acs_knn6 <- knn(acsNorm_learn[,1:8], acsNorm_valid[,1:8], acsNorm_learn$HighIncome, k=50, prob = TRUE)
head(acs_knn6)## [1] 0 0 0 0 0 0
## Levels: 0 1table(acsNorm_valid$HighIncome, acs_knn6)## acs_knn6
## 0 1
## 0 7076 35
## 1 416 55pcol6 <- as.character(as.numeric(acsNorm_valid$HighIncome1))
pairs(acsNorm_valid[1:8], pch = pcol6, col = c("green3", "red")
[(acsNorm_valid$HighIncome1 != acs_knn6)+1])
knn6_cm6_pred <- confusionMatrix(acs_knn6, acsNorm_valid$HighIncome, positive = "1")
knn6_cm6_pred## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 7076 416
## 1 35 55
##
## Accuracy : 0.9405
## 95% CI : (0.935, 0.9457)
## No Information Rate : 0.9379
## P-Value [Acc > NIR] : 0.177
##
## Kappa : 0.1797
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.116773
## Specificity : 0.995078
## Pos Pred Value : 0.611111
## Neg Pred Value : 0.944474
## Prevalence : 0.062121
## Detection Rate : 0.007254
## Detection Prevalence : 0.011870
## Balanced Accuracy : 0.555925
##
## 'Positive' Class : 1
## K nearest neighbor decision
As I increase k the accuracy increases until I chose k = 50. I could continue to repeat this property or (loop) to find the best k value where change in accuracy = 0 (first derivative of the function).
One thing to be carefule of is that the higher the k value the more complex the “outline” of the determinations.
I would also think it be valuable to change the variables included in knn. I only did this with two sets of variables, and mostly focused on changing the size of k.
Based on the knn I created I would select knn5 - I read that for the number of observations around 1000 that ideally k = 20 (roughly). Not a hard and fast rule, but worth choosing based on the common standard.
Comments on logit and linear regression model
My linear model does estimate negative incomes, which is not logically or stastically sound However, the purpose is to find best predictive model. So I ignored this to see how accurate I could predict High Income I also created multiple linear regressions, and chose this one. I based my decision on R-squared and changes in adjusted R- squared as I added/subtracted variables.
Best regression model = linear regression model 2 - based on accuracy at .941 (null model = .9389) and sensitivity at .23277